Science Guardian

Paradigms and power in science and society

Comparing mainstream claims with the literature, we defend honest, accomplished and independent minded scientists (Peter Duesberg, Harvey Bialy, Kary Mullis, Jim Watson, Peter Medawar, Erwin Chargaff, Richard Feynman, Linus Pauling, James Hansen, Fred Singer, Richard Lindzer, Rainer Plaga, Otto Rossler, Michio Kaku, David Rasnick, Rebecca Culshaw, Ernst Krebs, Mark Leggett, Adrian Kent) and their good science against ad hominem propaganda, overwhelming group psychology and internal science politics in the paradigm wars of cancer, HIV/AIDS, evolution, global warming, collider physics, health and nutrition, measuring truth only by the professional scholarly literature in peer reviewed journals, well researched books, and investigative reporting and reviews by thoughtful and informed academics, philosophers, researchers, scholars, authors, and journalists (Celia Farber, Liam Scheff, Robert Houston, Anthony Liversidge, James Blodgett, Jim Tankersley, John Tierney, Bob Herbert, Dennis Overbye, Marcus Cohen, Gary Null, Walter Wagner, Luis Sancho, Toby Ord and Eric Johnson).

Honest inquiry after truth, which is the noblest calling of the noblest men. – Arthur Schopenhauer

What is wanted is not the will to believe, but the wish to find out, which is the exact opposite. - Bertrand Russell

More Quotations on Science and Belief

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(Incorporating New AIDS Review)

House of Numbers is quietly explosive

September 5th, 2009

Remarkable movie shows how AIDS story falls apart under questioning

Leading luminaries confess flaws, confirming critics’ concerns

Clarity and entertainment value may gain wide audience for documentary

But John Moore and his squad are on the job to sink it if possible

shipoffoolsHouse of Numbers premiered last night at the Quad in New York City, and contrary to the uninformed review by Jeannette Catsoulis in the New York Times (see previous post), the documentary is a winner on every level – clarity of exposition, entertainment value, and unexpected revelation. Small wonder it has started garnering prizes at festivals (six so far).

Brent Leung adopts the Boy Scout approach of innocent inquiry, and travels the world in search of answers to the huge questions that HIV/AIDS ideology raises in every inquiring mind. He ends up gaining remarkable admissions from some leading lights in the field.

Web of inconsistency

The impression left as the credits roll is that every time he pokes at the supposedly solid science of HIV/AIDS he finds he meets no resistance, and his finger tears another hole is what seems like a cobweb of false claims, one that needs sweeping away before it catches another million hapless “HIV positives” to feed killer drugs to and, the film implies, shorten their lives for no good purpose except to preserve the careers and salaries of all in the vast economy of this statistically exaggerated and medically misread disease.

The film makes all the major points that the much vilified (by HIV defenders) “denialists” have made over the years, starting with Peter Duesberg’s brilliant and unrefuted reviews of the late 1980s, which have been censored from public attention ever since by Anthony Fauci of NIAID and the editors of the New York Times. But none of these McCarthy-ite internal politics are touched on in the film, which keeps it all very simple.

Conjuring the statistics

Can electron microscope images of the AIDS virus be produced? A leading expert in the technique shows Leung all the pictures produced by Gallo and by others since, but confirms they are only “probably” HIV. Do any tests provably confirm the presence of HIV or even HIV antibodies in the blood of “HIV positives”? No they don’t, other experts admit.

As the scientists quarrel on camera about which combination of tests might be definitive, it emerges that all tests, even PCR tests, have package disclaimers saying that in themselves they confirm nothing about the HIV status of the individual. Meanwhile, test interpretation varies by country, and by the information you have given the tester (are you gay? are you poor?). Rapid tests, used widely now in South Africa, are unreliable and prove nothing, it turns out, though Brent takes one on camera. Many Africans are still judged to be AIDS victims without any testing at all (the Bangui definition is still widely used, he discovers, for symptoms as simple as diarrhea and fever, no testing required).

James Chin, who was chief epidemiologist for WHO for five years, says he warned headquarters how flimsy the statistics were but no one paid any attention. Now he predicts that their “house of numbers” will collapse as the true situation emerges, and indeed huge downward adjustments have been made by the UN for the total of HIV “positives” in the world. (Kevin De Cock, the WHO official who stated a couple of years ago, that heterosexuals have never in reality been threatened by AIDS is not mentioned.)

With Brent and his audience thus instructed how a positive status doesn’t necessarily mean they are infected or have ever been infected by HIV, he is then shown how damaging and even lethal the drugs administered are. Reducing the dosage of the dreaded AZT in the nineties by substituting David Ho’s cocktail of protease inhibitors slowed patients’ decline, reprieving them from the early death guaranteed by full dose AZT before the mid nineties. Everyone lasted longer, so the triumph of protease inhibitors was applauded and the cause of AIDS spuriously confirmed. But deaths have continued at the same rate in the US since (about 17,000 a year). Meanwhile the definition of AIDS was expanded so that a decline was turned into a doubling of cases.

Applause during the film

By the time the film contemplates the experience of Steve and Sherrill Nagel the audience is ready to be horrified. The Nagels adopted a baby from Romania who tested positive in the US, and dutifully fed her AZT while doctors predicted she would barely last till age two. Her leg pains, loss of coordination, and mental disruption are disturbing to watch, and the parents finally decide that even by the measure of standard AIDS ideology it is not worth harming the child any further with AZT. There was a burst of applause at the premiere when it is announced that the child is now 19 and perfectly healthy.

The film doesn’t leave room for any official rebuttal of this or other anecdotes, but on the core points of the science and its politics well known figures such as Anthony Fauci of NIAID are given time to rebut the cynics. When they contradict themselves this is shown clearly. But what is most surprising is that Martin Delaney, who turned from being a skeptic to a staunch advocate of AIDS drugs when his San Francisco group Project Inform gained drug company funding, expresses a lot of world weary doubts about their usefulness and even notes that the companies have no financial motivation to think up a better way to go.

Montagnier’s stunning statement

In its final phase Brent Leung maps AIDS worldwide and shows how it matches poverty and how lack of good food and hygiene gives rise to exactly the same symptoms that are laid at the door of HIV. Is it possible, he asks, that much of global AIDS is sickness from poverty, and would be cured by pouring money into clean water and decent food rather than damaging drugs? That the drugs are damaging is earlier highlighted by photos of buffalo humps and by the death of Joyce Hafford after only 39 days in a test of nevirapine, with grotesque skin symptoms.

Ship of Fools by Joel Peter Witkin, or possibly the current situation in HIV/AIDS
The establishment in HIV/AIDS has practiced answers to all this, to be sure, though none of them bear examination, as we have found in writing this blog. So perhaps Brent Leung can be forgiven for not including them, although they are undoubtedly among the 300 hours of film he has recorded. What he has produced is a vivid documentation of unanswered – in fact, confirmed – doubts about the scientific rationale peddled in HIV/AIDS, conflicting claims by experts, and real people examples of ignorance and suffering. He has shown how AIDS drugs could equally be causing the same and worse symptoms and deaths as HIV is supposedly causing.

The climax of the film comes with Luc Montagnier assuring him that “a good immune system” can rid the body of HIV in a few weeks. Leung gets him to repeat this unexpected statement and then asks if it applies to poor Africans. If their immune systems are restored with adequate nutrition, would their bodies conquer HIV too? The soon to be Nobelist Montagnier says “I would think so.”

Montagnier also emphasizes as he has done over the years (he was barred from the San Francisco AIDS Conference for it) that a co-factor is always necessary for HIV to do its deadly work, which opens the possibility that HIV itself is not actually involved. Presumably now that he alone won the Nobel last year for discovering HIV “the cause of AIDS” he will now be less frank in public. But here he is on film. The cat is out of the bag.

Will the doc be stopped?

This is the kind of paradigm threatening conclusion that a huge array of vested interests cannot abide, ranging from the emotions of patients who have committed themselves to taking the drugs to the vast array of career and financial interests that need to keep the 25 year old HIV/AIDS ideology in play, including now George Bush and Bill Clinton, who have both sought redemption through AIDS funding.

John Moore of Cornell, the HIV scientist most hostile in public and behind the scenes to outside review, has vowed in email to them that the filmmakers will, as the Hollywood phrase has it, ‘never eat lunch in this town again.’ Yet his efforts haven’t been able to stop their momentum so far, despite his supporters at the Times, which itself now has a huge, 25 year investment in the status quo.

With the politics so intense the censors of AIDS review may still succeed, but on behalf of the public Leung has fired the loudest shot yet across the bows of the great ship of fools, SS HIV Science. It is hard to imagine that, as has already happened, thoughtful people completely unaware of the real situation before they take their seats won’t leave the cinema skeptical of and even hostile to those that want to shut off public debate.

And the irony is that Leung has done nothing but document the tale that HIV scientists tell against themselves. The confusion he records looks amusingly like the Mad Hatters tea party from Alice in Wonderland. Could it be that they have led the world through a looking glass for 25 years?

Entertainment plus important revelation. All in all, a stunning achievement.

Sloppy science everywhere

September 21st, 2007

Hotz at Journal initiates wave of media coverage of error in science

Hotter the field, the more bias

Most studies wrong

error-sign.jpegAttentive perusers of this modest blog may have noticed that we recently expanded its subhead to include the thought that while we base our critique of the public claims of Robert Gallo, Anthony Fauci, John P. Moore, Mark Wainberg, Nancy Padian and other highly decorated generals of the HIV∫AIDS salvation army on the peer-reviewed literature, a certain caveat is in order.

Not everything which finds its way into science and medical journals, even the top ones, is totally reliable, because even if the authors are not conscious of being emotionally flawed human beings subject to all the warping influences listed in the blogo above, their best efforts would still include bad design, inadvertent error and unconscious “data management”, perhaps because they make false assumptions at the start of the study, a habit which is universal in HIV∫AIDS.

As we have mentioned earlier one of the more distinguished scientists we have been privileged to interview, the renowned Harvard researcher and Nobel prize winner Walter Gilbert, once confided to us that whenever he embarked on a new investigation prompted by someone else’s paper he would always try to repeat the experiment himself, and was surprisingly often chagrined to find that he couldn’t.

And in our early efforts to report on the objections raised by the equally distinguished retrovirology researcher Peter Duesberg of Berkeley to the theoretical kite flown by Robert Gallo in 1984 in AIDS, the unlikely notion that the ugly and fatal new syndrome of immune collapse was cause by an infectious virus eventually labeled Human Immunodeficiency Virus, unfortunately immediately backed by the federal government and thus rendered sacrosanct, we were taken aback by the deep analysis of papers in HIV∫AIDS that the Berkeley professor frequently explained to us privately which showed they were badly done and poorly argued and as a result entirely misleading, even if one accepted the uncritical assumption that they were all based upon, that HIV was the right culprit for the new and appalling disease.

Politely ignoring a huge problem

We also noted, however, that in arguing against the HIV=AIDS paradigm, professor Duesberg did not at first rely on exposing the shoddiness of the papers that resulted from it. He would directly undermine the paradigm by accepting the data and conclusions of the literature, and then show how the paradigm did not stack up – in fact was contradicted by the very papers that were claimed to shore it up.

Only later was he forced to show how many major results were based on poorly designed studies which were misinterpreted, an obligation unfairly thrust upon him in answering the somewhat specious demand, Well if it isn’t HIV, what is it that causes AIDS, then? The demand is specious because so much of the literature is based on the assumption that it is HIV which is the villain in the drama, that most of it will have to be redone without that assumption to nail down the real and obviously multiple causes of immune failure in all five continents, with all their disparate symptoms and epidemiology.

A mudslide of articles about error

Anyhow we are pleased to notice that a rash of articles came out this week publicizing this little noticed fact, that it is not simply fraud which occasionally corrupts the peer-reviewed literature, it is the inadequacy of peer review, which often lets go by papers which should have been corrected or redone, whose conclusions are unreliable.

Needless to say, one of the marks of the horrendously incompetent science reporting carried out in the media – reporting that mostly doesn’t rise above the level of noting down and publishing what sources say without it passing through the critical faculties of the reporter, assuming that these even exist, let alone actually double checking it with critics in the traditional manner observed in every other field of public affairs – is that none of the top reporters whose specialty HIV=AIDS is, with the exception of HIV skeptic Celia Farber in Harpers, and of course HIV skeptic Liam Scheff elsewhere, has shown any interest whatsoever in the possibility that research in the field is questionable.

It is as if they either didn’t know, or have given the NIAID under the firm control of Lasker winner Dr Anthony Fauci a free pass, for some reason, possibly one associated with the undeniable hostility of that public servant to such notions.

How wrong it is to assume that published, peer reviewed science is scripture engraved in tablets of stone is well known to those familiar with the Baltimore scandal, where Nobelist David Baltimore blocked retraction of an incorrect paper with his name on it for years until three Congressional investigations finally prised his protective grip from it. Whether error or knowing fraud (by the lead author, not Baltimore) was involved was not quite made clear, but the subsequent book by Daniel Kevles exonerated Dr Baltimore sufficiently that having been ignominiously kicked out of the presidency of Rockefeller University, eventually the renowned researcher was able to be reinstated in the eyes of the public with the presidency of Caltech, from which he recently retired, where professor Kevles also moved from Yale.

Hotz’ hot column points to Ioannidis’s white hot essay

But fraud is not an interesting subject to contemplate, even if the cases of it which are occasionally exposed in the public prints are often spectacular, as in the case of the downfall of the Korean gentleman recently. The important point is that bad but not intentionally fraudulent science gets into print even in the top journals, as HIV/AIDS has shown in its own spectacular fashion, and science reporters seem universally unaware of this possibility. Now however, we have more than one article suddenly acknowledging this problem.

The first was last Friday, when the Wall Street Journal printed a column by Robert Lee Hotz, Most Science Studies Appear to Be Tainted By Sloppy Analysis, reporting on the work of John Ioannidis, an epidemiologist who studies research methods at the University of Ioannina School of Medicine in Greece and Tufts University in Medford, Mass.

ioannidis.jpgIoannidis has documented how the conclusions of thousands of peer-reviewed research papers may be invalid because the research is inept. In fact, he is the star of the Public Library of Science, where his stunningly honest essay of 2005, Why Most Published Research Findings Are False is their most downloaded technical paper, which is clearly what prompted Hotz’ column.

The essay is a strong contrast with Tara C. Smith and Steven Novella’s froglike masterpiece which we are deconstructing here when more important matters do not obtrude, as in the case of this exemplary piece of research based, logically sound, statistically formulated and politically sophisticated scientific commentary:

Summary

There is increasing concern that most current published research findings are false. The probability that a research claim is true may depend on study power and bias, the number of other studies on the same question, and, importantly, the ratio of true to no relationships among the relationships probed in each scientific field. In this framework, a research finding is less likely to be true when the studies conducted in a field are smaller; when effect sizes are smaller; when there is a greater number and lesser preselection of tested relationships; where there is greater flexibility in designs, definitions, outcomes, and analytical modes; when there is greater financial and other interest and prejudice; and when more teams are involved in a scientific field in chase of statistical significance. Simulations show that for most study designs and settings, it is more likely for a research claim to be false than true. Moreover, for many current scientific fields, claimed research findings may often be simply accurate measures of the prevailing bias….

Published research findings are sometimes refuted by subsequent evidence, with ensuing confusion and disappointment. Refutation and controversy is seen across the range of research designs, from clinical trials and traditional epidemiological studies [1–3] to the most modern molecular research [4,5]. There is increasing concern that in modern research, false findings may be the majority or even the vast majority of published research claims [6–8]. However, this should not be surprising. It can be proven that most claimed research findings are false. …..

Bias

First, let us define bias as the combination of various design, data, analysis, and presentation factors that tend to produce research findings when they should not be produced…..

Corollary 4: The greater the flexibility in designs, definitions, outcomes, and analytical modes in a scientific field, the less likely the research findings are to be true. Flexibility increases the potential for transforming what would be “negative” results into “positive” results, i.e., bias, u.…..


Corollary 5: The greater the financial and other interests and prejudices in a scientific field, the less likely the research findings are to be true. Conflicts of interest and prejudice may increase bias, u. Conflicts of interest are very common in biomedical research [26], and typically they are inadequately and sparsely reported [26,27]. Prejudice may not necessarily have financial roots. Scientists in a given field may be prejudiced purely because of their belief in a scientific theory or commitment to their own findings. Many otherwise seemingly independent, university-based studies may be conducted for no other reason than to give physicians and researchers qualifications for promotion or tenure. Such nonfinancial conflicts may also lead to distorted reported results and interpretations. Prestigious investigators may suppress via the peer review process the appearance and dissemination of findings that refute their findings, thus condemning their field to perpetuate false dogma. Empirical evidence on expert opinion shows that it is extremely unreliable [28].


Corollary 6: The hotter a scientific field (with more scientific teams involved), the less likely the research findings are to be true….

Most Research Findings Are False for Most Research Designs and for Most Fields

Claimed Research Findings May Often Be Simply Accurate Measures of the Prevailing Bias

Traditionally, investigators have viewed large and highly significant effects with excitement, as signs of important discoveries. Too large and too highly significant effects may actually be more likely to be signs of large bias in most fields of modern research. They should lead investigators to careful critical thinking about what might have gone wrong with their data, analyses, and results.

Of course, investigators working in any field are likely to resist accepting that the whole field in which they have spent their careers is a “null field.” However, other lines of evidence, or advances in technology and experimentation, may lead eventually to the dismantling of a scientific field….

How Can We Improve the Situation?

Is it unavoidable that most research findings are false, or can we improve the situation? A major problem is that it is impossible to know with 100% certainty what the truth is in any research question….

Large-scale evidence is also particularly indicated when it can test major concepts rather than narrow, specific questions. A negative finding can then refute not only a specific proposed claim, but a whole field or considerable portion thereof. Selecting the performance of large-scale studies based on narrow-minded criteria, such as the marketing promotion of a specific drug, is largely wasted research.

What matters is the totality of the evidence. Diminishing bias through enhanced research standards and curtailing of prejudices may also help. However, this may require a change in scientific mentality that might be difficult to achieve.

Finally, instead of chasing statistical significance, we should improve our understanding of the range of R values—the pre-study odds—where research efforts operate [10]. Before running an experiment, investigators should consider what they believe the chances are that they are testing a true rather than a non-true relationship. Speculated high R values may sometimes then be ascertained. As described above, whenever ethically acceptable, large studies with minimal bias should be performed on research findings that are considered relatively established, to see how often they are indeed confirmed. I suspect several established “classics” will fail the test [36].

Nevertheless, most new discoveries will continue to stem from hypothesis-generating research with low or very low pre-study odds. We should then acknowledge that statistical significance testing in the report of a single study gives only a partial picture, without knowing how much testing has been done outside the report and in the relevant field at large.

Human error in papers

Here is how Hotz in Most Science Studies Appear to Be Tainted By Sloppy Analysis told the many readers of the pragmatic Wall Street Journal about this problem, thus ensuring that many investors, lawyers, and other people who need realistic information about scientific claims of world pandemics are now aware that scientists’ pronouncements, and their published literature, may have to be double checked for accuracy, since the New York Times has a habit of not bothering to do so, not having the money or inclination to employ factcheckers since it trusts its reporters to get it right, since they have instant access after all to the top gurus of every field, and judging from their public appearances do not appear to be overworked:

Most Science Studies Appear to Be Tainted By Sloppy Analysis

We all make mistakes and, if you believe medical scholar John Ioannidis, scientists make more than their fair share. By his calculations, most published research findings are wrong.

Dr. Ioannidis is an epidemiologist who studies research methods at the University of Ioannina School of Medicine in Greece and Tufts University in Medford, Mass. In a series of influential analytical reports, he has documented how, in thousands of peer-reviewed research papers published every year, there may be so much less than meets the eye.

These flawed findings, for the most part, stem not from fraud or formal misconduct, but from more mundane misbehavior: miscalculation, poor study design or self-serving data analysis. “There is an increasing concern that in modern research, false findings may be the majority or even the vast majority of published research claims,” Dr. Ioannidis said. “A new claim about a research finding is more likely to be false than true.”

The hotter the field of research the more likely its published findings should be viewed skeptically, he determined.

…”There is an increasing concern that in modern research, false findings may be the majority or even the vast majority of published research claims,” Dr. Ioannidis said. “A new claim about a research finding is more likely to be false than true.”

Hotz dug around and found plenty of agreement with what Ioannidis is saying, and plenty of material to confirm what the Greek American researcher has found in his many reports:

Take the discovery that the risk of disease may vary between men and women, depending on their genes. Studies have prominently reported such sex differences for hypertension, schizophrenia and multiple sclerosis, as well as lung cancer and heart attacks. In research published last month in the Journal of the American Medical Association, Dr. Ioannidis and his colleagues analyzed 432 published research claims concerning gender and genes (Drs. Nikolaos A. Patsopoulos, Athina Tatsioni and John Ioannidis analyzed claims of genetic risk and sex differences in “Claims of Sex Differences: An Empirical Assessment in Genetic Associations,”3 (abstract; login required for full text) published in the Journal of the American Medical Association last month).

Upon closer scrutiny, almost none of them held up. Only one was replicated.

What’s going wrong? The key problem is one most observers of science are well aware of, and that is that science advances hypothesis by hypothesis, which tends to translate into hope by hope, and the data tends to support a new hypothesis unless studies are carefully done to banish that effect:

Statistically speaking, science suffers from an excess of significance. Overeager researchers often tinker too much with the statistical variables of their analysis to coax any meaningful insight from their data sets. “People are messing around with the data to find anything that seems significant, to show they have found something that is new and unusual,” Dr. Ioannidis said.

In the U. S., research is a $55-billion-a-year enterprise that stakes its credibility on the reliability of evidence and the work of Dr. Ioannidis strikes a raw nerve. In fact, his 2005 essay “Why Most Published Research Findings Are False” remains the most downloaded technical paper that the journal PLoS Medicine has ever published.

“He has done systematic looks at the published literature and empirically shown us what we know deep inside our hearts,” said Muin Khoury, director of the National Office of Public Health Genomics at the U.S. Centers for Disease Control and Prevention. “We need to pay more attention to the replication of published scientific results.”

Every new fact discovered through experiment represents a foothold in the unknown. In a wilderness of knowledge, it can be difficult to distinguish error from fraud, sloppiness from deception, eagerness from greed or, increasingly, scientific conviction from partisan passion. As scientific findings become fodder for political policy wars over matters from stem-cell research to global warming, even trivial errors and corrections can have larger consequences.

Still, other researchers warn not to fear all mistakes. Error is as much a part of science as discovery. It is the inevitable byproduct of a search for truth that must proceed by trial and error. “Where you have new areas of knowledge developing, then the science is going to be disputed, subject to errors arising from inadequate data or the failure to recognize new matters,” said Yale University science historian Daniel Kevles. Conflicting data and differences of interpretation are common.

Now in his well worded piece Hotz comes to the point where HIV/AIDS critics will sit up and applaud:(our boldface)

To root out mistakes, scientists rely on each other to be vigilant. Even so, findings too rarely are checked by others or independently replicated. Retractions, while more common, are still relatively infrequent. Findings that have been refuted can linger in the scientific literature for years to be cited unwittingly by other researchers, compounding the errors.

Stung by frauds in physics, biology and medicine, research journals recently adopted more stringent safeguards to protect at least against deliberate fabrication of data. But it is hard to admit even honest error. Last month, the Chinese government proposed a new law to allow its scientists to admit failures without penalty. Next week, the first world conference on research integrity convenes in Lisbon.

Overall, technical reviewers are hard-pressed to detect every anomaly. On average, researchers submit about 12,000 papers annually just to the weekly peer-reviewed journal Science. Last year, four papers in Science were retracted. A dozen others were corrected.

No one actually knows how many incorrect research reports remain unchallenged.

Earlier this year, informatics expert Murat Cokol and his colleagues at Columbia University sorted through 9.4 million research papers at the U.S. National Library of Medicine published from 1950 through 2004 in 4,000 journals. By raw count, just 596 had been formally retracted, Dr. Cokol reported.

“The correction isn’t the ultimate truth either,” Prof. Kevles said.

Well, how many were wrong? That is the unanswered question. If all the papers on HIV/AIDS were immediately retracted because HIV is clearly not involved in causing immune collapse, Science would be crippled as a reference source, and science would lose much of its credibility. An honest error on the part of the editors, perhaps, but inexcusable as long as they claim the role of the gatekeepers and the watchdogs of science.

All of this speaks for the credibility of the well qualified critics of the paradigm in HIV=AIDS and the unusual attention they have paid to the quality of the research papers which support it, where they have found a remarkable level of data mismanagement, poor design and misleading conclusions. Yet their case is typically dismissed by paradigm defenders such as Tara Smoth of Iowa, Steve Connall of Yale, John P. Moore of Weill Cornell with scorn and derision, rather than scientific arguments. The public likewise assumes that the literature is thoroughly validated by peer review.

Now the public has been informed by one prominent newspaper, perhaps the most trusted daily now, that something is rotten in the state of science, and that they should proceed with caution before dismissing all challenges to mainstream science as if they were all ignorant creationism. After all, it is clear now that the paradigm HIV causes AIDS would have been universally discredited long ago but for the papers universally based on the assumption they are used to support.

What’s to be done?

Most people, including almost all the scientists in a field, are unlikely to examine a paper closely enough to find its faults. One wonders just how many beliefs would be dashed if they did. Dr Ioannidis has already found that the new paradigm that the sexes differ in their risk of disease according to their gender is based on 432 studies of which only one was able to be replicated and proven valid.

It is difficult to know what to trust until all the papers on a topic are thoroughly reviewed for bias, and there is no field where bias is so blatant as HIV/AIDS, where scientists such as Moore and Wainberg are so proud of it that Wainberg has suggested imprisonment for the reviewers.

Apparently in one later paper in another PLoS Medicine article earlier this year, Ramal Moonesinghe and Muin Khoury at the U.S. Centers for Disease Control and Prevention demonstrated that the likelihood of a published research result being true increases when that finding has been repeatedly replicated in multiple studies. The article is: “Most Published Research Findings Are False — But a Little Replication Goes a Long Way.

But with bias and preconceptions playing a big part obviously repetition is not enough. Raising the level of awareness among scientists and the public of the fallibility of science is key. Lets hope that the Conference last week in the world capital of port, the world’s most delicious liqueur, started some greater awareness of the problem and improvement of the situation in science. The European Science Foundation and the Office of Research Integrity held a world conference on research integrity in Lisbon, Portugal, Sept. 16-19, 2007, which included papers on best practices, training researchers, and the role played by academic journals).

Gee, we wondered if anyone mentioned HIV/AIDS in this context? Not only is it a field where bias in favor of the unproven and unsubstantiated hypothesis is so rife that every paper is imbued with it, and researchers flaunt their bias as if it was a badge of honor, but as regards testing drugs, there haven’t been any controls in any study after the AZT study was called to a sudden halt twenty years ago because the benefit was so powerfully assumed by gay activists that they insisted that the scientists release the drug immediately without further testing because it would be unfair to withhold it from the placebo control group, who were already finding ways to take it.

This blatant lack of controls is one reason why the drugs in AIDS are not recognized as being as lethal as general studies of the welfare of patients show they are, with half of current AIDS deaths due to the drugs and not to AIDS proper, whatever the cause of that is.

Of course, to those unaware that the scientific literature is subject to human error, that last phrase will come as a surprise.

Here is Hotz’s piece for reference:
September 14, 2007

SCIENCE JOURNAL
By ROBERT LEE HOTZ

Most Science Studies
Appear to Be Tainted
By Sloppy Analysis
September 14, 2007; Page B1

We all make mistakes and, if you believe medical scholar John Ioannidis, scientists make more than their fair share. By his calculations, most published research findings are wrong.

Dr. Ioannidis is an epidemiologist who studies research methods at the University of Ioannina School of Medicine in Greece and Tufts University in Medford, Mass. In a series of influential analytical reports, he has documented how, in thousands of peer-reviewed research papers published every year, there may be so much less than meets the eye.

These flawed findings, for the most part, stem not from fraud or formal misconduct, but from more mundane misbehavior: miscalculation, poor study design or self-serving data analysis. “There is an increasing concern that in modern research, false findings may be the majority or even the vast majority of published research claims,” Dr. Ioannidis said. “A new claim about a research finding is more likely to be false than true.”

The hotter the field of research the more likely its published findings should be viewed skeptically, he determined.

Take the discovery that the risk of disease may vary between men and women, depending on their genes. Studies have prominently reported such sex differences for hypertension, schizophrenia and multiple sclerosis, as well as lung cancer and heart attacks. In research published last month in the Journal of the American Medical Association, Dr. Ioannidis and his colleagues analyzed 432 published research claims concerning gender and genes.
——————————-
RECOMMENDED READING

–by Robert Lee Hotz
[Recommended Reading]
Drs. Nikolaos A. Patsopoulos, Athina Tatsioni and John Ioannidis analyzed claims of genetic risk and sex differences in “Claims of Sex Differences: An Empirical Assessment in Genetic Associations,”3 (abstract; login required for full text) published in the Journal of the American Medical Association last month.
* * *
Dr. John Ioannidis argued that false findings may be the majority of published research claims, in “Why Most Published Research Findings Are False,”4 in the PLoS Medicine journal, in August 2005.
* * *
In another PLoS Medicine article earlier this year, Ramal Moonesinghe and Muin Khoury at the U.S. Centers for Disease Control and Prevention demonstrated that the likelihood of a published research result being true increases when that finding has been repeatedly replicated in multiple studies. The article is: “Most Published Research Findings Are False — But a Little Replication Goes a Long Way.”5
* * *
The Office of Research Integrity6 promotes integrity in biomedical and behavioral research supported by the U.S. Public Health Service at about 4,000 institutions world-wide.
* * *
The European Science Foundation and the Office of Research Integrity are holding a world conference on research integrity7 in Lisbon, Portugal, Sept. 16-19, 2007. The invited researchers will be presenting papers on best practices, training researchers, and the role played by academic journals.
———————————————————————

Upon closer scrutiny, almost none of them held up. Only one was replicated.

Statistically speaking, science suffers from an excess of significance. Overeager researchers often tinker too much with the statistical variables of their analysis to coax any meaningful insight from their data sets. “People are messing around with the data to find anything that seems significant, to show they have found something that is new and unusual,” Dr. Ioannidis said.

In the U. S., research is a $55-billion-a-year enterprise that stakes its credibility on the reliability of evidence and the work of Dr. Ioannidis strikes a raw nerve. In fact, his 2005 essay “Why Most Published Research Findings Are False” remains the most downloaded technical paper that the journal PLoS Medicine has ever published.

“He has done systematic looks at the published literature and empirically shown us what we know deep inside our hearts,” said Muin Khoury, director of the National Office of Public Health Genomics at the U.S. Centers for Disease Control and Prevention. “We need to pay more attention to the replication of published scientific results.”

Every new fact discovered through experiment represents a foothold in the unknown. In a wilderness of knowledge, it can be difficult to distinguish error from fraud, sloppiness from deception, eagerness from greed or, increasingly, scientific conviction from partisan passion. As scientific findings become fodder for political policy wars over matters from stem-cell research to global warming, even trivial errors and corrections can have larger consequences.

Still, other researchers warn not to fear all mistakes. Error is as much a part of science as discovery. It is the inevitable byproduct of a search for truth that must proceed by trial and error. “Where you have new areas of knowledge developing, then the science is going to be disputed, subject to errors arising from inadequate data or the failure to recognize new matters,” said Yale University science historian Daniel Kevles. Conflicting data and differences of interpretation are common.

To root out mistakes, scientists rely on each other to be vigilant. Even so, findings too rarely are checked by others or independently replicated. Retractions, while more common, are still relatively infrequent. Findings that have been refuted can linger in the scientific literature for years to be cited unwittingly by other researchers, compounding the errors.

Stung by frauds in physics, biology and medicine, research journals recently adopted more stringent safeguards to protect at least against deliberate fabrication of data. But it is hard to admit even honest error. Last month, the Chinese government proposed a new law to allow its scientists to admit failures without penalty. Next week, the first world conference on research integrity convenes in Lisbon.

Overall, technical reviewers are hard-pressed to detect every anomaly. On average, researchers submit about 12,000 papers annually just to the weekly peer-reviewed journal Science. Last year, four papers in Science were retracted. A dozen others were corrected.

No one actually knows how many incorrect research reports remain unchallenged.

Earlier this year, informatics expert Murat Cokol and his colleagues at Columbia University sorted through 9.4 million research papers at the U.S. National Library of Medicine published from 1950 through 2004 in 4,000 journals. By raw count, just 596 had been formally retracted, Dr. Cokol reported.

“The correction isn’t the ultimate truth either,” Prof. Kevles said.

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Here for reference is the complete essay by Ionnadis, Why Most Published Research Findings Are False. The boldface is added by NAR to highlight key passages:
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PLoS Medicine
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ESSAY

Why Most Published Research Findings Are False

John P. A. Ioannidis

Summary

There is increasing concern that most current published research findings are false. The probability that a research claim is true may depend on study power and bias, the number of other studies on the same question, and, importantly, the ratio of true to no relationships among the relationships probed in each scientific field. In this framework, a research finding is less likely to be true when the studies conducted in a field are smaller; when effect sizes are smaller; when there is a greater number and lesser preselection of tested relationships; where there is greater flexibility in designs, definitions, outcomes, and analytical modes; when there is greater financial and other interest and prejudice; and when more teams are involved in a scientific field in chase of statistical significance. Simulations show that for most study designs and settings, it is more likely for a research claim to be false than true. Moreover, for many current scientific fields, claimed research findings may often be simply accurate measures of the prevailing bias. In this essay, I discuss the implications of these problems for the conduct and interpretation of research.

Competing Interests: The author has declared that no competing interests exist.

Citation: Ioannidis JPA (2005) Why Most Published Research Findings Are False. PLoS Med 2(8): e124 doi:10.1371/journal.pmed.0020124

Published: August 30, 2005

Copyright: © 2005 John P. A. Ioannidis. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abbreviation: PPV, positive predictive value

John P. A. Ioannidis is in the Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece, and Institute for Clinical Research and Health Policy Studies, Department of Medicine, Tufts-New England Medical Center, Tufts University School of Medicine, Boston, Massachusetts, United States of America. E-mail: jioannid@cc.uoi.gr

Published research findings are sometimes refuted by subsequent evidence, with ensuing confusion and disappointment. Refutation and controversy is seen across the range of research designs, from clinical trials and traditional epidemiological studies [1–3] to the most modern molecular research [4,5]. There is increasing concern that in modern research, false findings may be the majority or even the vast majority of published research claims [6–8]. However, this should not be surprising. It can be proven that most claimed research findings are false. Here I will examine the key factors that influence this problem and some corollaries thereof.

Modeling the Framework for False Positive Findings

Several methodologists have pointed out [9–11] that the high rate of nonreplication (lack of confirmation) of research discoveries is a consequence of the convenient, yet ill-founded strategy of claiming conclusive research findings solely on the basis of a single study assessed by formal statistical significance, typically for a p-value less than 0.05. Research is not most appropriately represented and summarized by p-values, but, unfortunately, there is a widespread notion that medical research articles should be interpreted based only on p-values. Research findings are defined here as any relationship reaching formal statistical significance, e.g., effective interventions, informative predictors, risk factors, or associations. “Negative” research is also very useful. “Negative” is actually a misnomer, and the misinterpretation is widespread. However, here we will target relationships that investigators claim exist, rather than null findings.

It can be proven that most claimed research findings are false.

As has been shown previously, the probability that a research finding is indeed true depends on the prior probability of it being true (before doing the study), the statistical power of the study, and the level of statistical significance [10,11]. Consider a 2 × 2 table in which research findings are compared against the gold standard of true relationships in a scientific field. In a research field both true and false hypotheses can be made about the presence of relationships. Let R be the ratio of the number of “true relationships” to “no relationships” among those tested in the field. R is characteristic of the field and can vary a lot depending on whether the field targets highly likely relationships or searches for only one or a few true relationships among thousands and millions of hypotheses that may be postulated. Let us also consider, for computational simplicity, circumscribed fields where either there is only one true relationship (among many that can be hypothesized) or the power is similar to find any of the several existing true relationships. The pre-study probability of a relationship being true is R/(R + 1). The probability of a study finding a true relationship reflects the power 1 − β (one minus the Type II error rate). The probability of claiming a relationship when none truly exists reflects the Type I error rate, α. Assuming that c relationships are being probed in the field, the expected values of the 2 × 2 table are given in Table 1. After a research finding has been claimed based on achieving formal statistical significance, the post-study probability that it is true is the positive predictive value, PPV. The PPV is also the complementary probability of what Wacholder et al. have called the false positive report probability [10]. According to the 2 × 2 table, one gets PPV = (1 − β)R/(R − βR + α). A research finding is thus more likely true than false if (1 − β)R > α. Since usually the vast majority of investigators depend on α = 0.05, this means that a research finding is more likely true than false if (1 − β)R > 0.05.

Table 1. Research Findings and True Relationships

What is less well appreciated is that bias and the extent of repeated independent testing by different teams of investigators around the globe may further distort this picture and may lead to even smaller probabilities of the research findings being indeed true. We will try to model these two factors in the context of similar 2 × 2 tables.

Bias

First, let us define bias as the combination of various design, data, analysis, and presentation factors that tend to produce research findings when they should not be produced. Let u be the proportion of probed analyses that would not have been “research findings,” but nevertheless end up presented and reported as such, because of bias. Bias should not be confused with chance variability that causes some findings to be false by chance even though the study design, data, analysis, and presentation are perfect. Bias can entail manipulation in the analysis or reporting of findings. Selective or distorted reporting is a typical form of such bias. We may assume that u does not depend on whether a true relationship exists or not. This is not an unreasonable assumption, since typically it is impossible to know which relationships are indeed true. In the presence of bias (Table 2), one gets PPV = ([1 − β]R + uβR)/(R + α − βR + u − uα + uβR), and PPV decreases with increasing u, unless 1 − β ≤ α, i.e., 1 − β ≤ 0.05 for most situations. Thus, with increasing bias, the chances that a research finding is true diminish considerably. This is shown for different levels of power and for different pre-study odds in Figure 1.
Figure 1. PPV (Probability That a Research Finding Is True) as a Function of the Pre-Study Odds for Various Levels of Bias, u

Panels correspond to power of 0.20, 0.50, and 0.80.

Table 2. Research Findings and True Relationships in the Presence of Bias

Conversely, true research findings may occasionally be annulled because of reverse bias. For example, with large measurement errors relationships are lost in noise [12], or investigators use data inefficiently or fail to notice statistically significant relationships, or there may be conflicts of interest that tend to “bury” significant findings [13]. There is no good large-scale empirical evidence on how frequently such reverse bias may occur across diverse research fields. However, it is probably fair to say that reverse bias is not as common. Moreover measurement errors and inefficient use of data are probably becoming less frequent problems, since measurement error has decreased with technological advances in the molecular era and investigators are becoming increasingly sophisticated about their data. Regardless, reverse bias may be modeled in the same way as bias above. Also reverse bias should not be confused with chance variability that may lead to missing a true relationship because of chance.

Testing by Several Independent Teams

Several independent teams may be addressing the same sets of research questions. As research efforts are globalized, it is practically the rule that several research teams, often dozens of them, may probe the same or similar questions. Unfortunately, in some areas, the prevailing mentality until now has been to focus on isolated discoveries by single teams and interpret research experiments in isolation. An increasing number of questions have at least one study claiming a research finding, and this receives unilateral attention. The probability that at least one study, among several done on the same question, claims a statistically significant research finding is easy to estimate. For n independent studies of equal power, the 2 × 2 table is shown in Table 3: PPV = R(1 − βn)/(R + 1 − [1 − α]n − Rβn) (not considering bias). With increasing number of independent studies, PPV tends to decrease, unless 1 − β < α, i.e., typically 1 − β < 0.05. This is shown for different levels of power and for different pre-study odds in Figure 2. For n studies of different power, the term βn is replaced by the product of the terms βi for i = 1 to n, but inferences are similar.
Figure 2. PPV (Probability That a Research Finding Is True) as a Function of the Pre-Study Odds for Various Numbers of Conducted Studies, n

Panels correspond to power of 0.20, 0.50, and 0.80.

Table 3. Research Findings and True Relationships in the Presence of Multiple Studies
Corollaries

A practical example is shown in Box 1. Based on the above considerations, one may deduce several interesting corollaries about the probability that a research finding is indeed true.

Corollary 1: The smaller the studies conducted in a scientific field, the less likely the research findings are to be true. Small sample size means smaller power and, for all functions above, the PPV for a true research finding decreases as power decreases towards 1 − β = 0.05. Thus, other factors being equal, research findings are more likely true in scientific fields that undertake large studies, such as randomized controlled trials in cardiology (several thousand subjects randomized) [14] than in scientific fields with small studies, such as most research of molecular predictors (sample sizes 100-fold smaller) [15].

Corollary 2: The smaller the effect sizes in a scientific field, the less likely the research findings are to be true. Power is also related to the effect size. Thus research findings are more likely true in scientific fields with large effects, such as the impact of smoking on cancer or cardiovascular disease (relative risks 3–20), than in scientific fields where postulated effects are small, such as genetic risk factors for multigenetic diseases (relative risks 1.1–1.5) [7]. Modern epidemiology is increasingly obliged to target smaller effect sizes [16]. Consequently, the proportion of true research findings is expected to decrease. In the same line of thinking, if the true effect sizes are very small in a scientific field, this field is likely to be plagued by almost ubiquitous false positive claims. For example, if the majority of true genetic or nutritional determinants of complex diseases confer relative risks less than 1.05, genetic or nutritional epidemiology would be largely utopian endeavors.

Corollary 3: The greater the number and the lesser the selection of tested relationships in a scientific field, the less likely the research findings are to be true. As shown above, the post-study probability that a finding is true (PPV) depends a lot on the pre-study odds (R). Thus, research findings are more likely true in confirmatory designs, such as large phase III randomized controlled trials, or meta-analyses thereof, than in hypothesis-generating experiments. Fields considered highly informative and creative given the wealth of the assembled and tested information, such as microarrays and other high-throughput discovery-oriented research [4,8,17], should have extremely low PPV.

Corollary 4: The greater the flexibility in designs, definitions, outcomes, and analytical modes in a scientific field, the less likely the research findings are to be true. Flexibility increases the potential for transforming what would be “negative” results into “positive” results, i.e., bias, u. For several research designs, e.g., randomized controlled trials [18–20] or meta-analyses [21,22], there have been efforts to standardize their conduct and reporting. Adherence to common standards is likely to increase the proportion of true findings. The same applies to outcomes. True findings may be more common when outcomes are unequivocal and universally agreed (e.g., death) rather than when multifarious outcomes are devised (e.g., scales for schizophrenia outcomes) [23]. Similarly, fields that use commonly agreed, stereotyped analytical methods (e.g., Kaplan-Meier plots and the log-rank test) [24] may yield a larger proportion of true findings than fields where analytical methods are still under experimentation (e.g., artificial intelligence methods) and only “best” results are reported. Regardless, even in the most stringent research designs, bias seems to be a major problem. For example, there is strong evidence that selective outcome reporting, with manipulation of the outcomes and analyses reported, is a common problem even for randomized trails [25]. Simply abolishing selective publication would not make this problem go away.

Corollary 5: The greater the financial and other interests and prejudices in a scientific field, the less likely the research findings are to be true. Conflicts of interest and prejudice may increase bias, u. Conflicts of interest are very common in biomedical research [26], and typically they are inadequately and sparsely reported [26,27]. Prejudice may not necessarily have financial roots. Scientists in a given field may be prejudiced purely because of their belief in a scientific theory or commitment to their own findings. Many otherwise seemingly independent, university-based studies may be conducted for no other reason than to give physicians and researchers qualifications for promotion or tenure. Such nonfinancial conflicts may also lead to distorted reported results and interpretations. Prestigious investigators may suppress via the peer review process the appearance and dissemination of findings that refute their findings, thus condemning their field to perpetuate false dogma. Empirical evidence on expert opinion shows that it is extremely unreliable [28].


Corollary 6: The hotter a scientific field (with more scientific teams involved), the less likely the research findings are to be true.
This seemingly paradoxical corollary follows because, as stated above, the PPV of isolated findings decreases when many teams of investigators are involved in the same field. This may explain why we occasionally see major excitement followed rapidly by severe disappointments in fields that draw wide attention. With many teams working on the same field and with massive experimental data being produced, timing is of the essence in beating competition. Thus, each team may prioritize on pursuing and disseminating its most impressive “positive” results. “Negative” results may become attractive for dissemination only if some other team has found a “positive” association on the same question. In that case, it may be attractive to refute a claim made in some prestigious journal. The term Proteus phenomenon has been coined to describe this phenomenon of rapidly alternating extreme research claims and extremely opposite refutations [29]. Empirical evidence suggests that this sequence of extreme opposites is very common in molecular genetics [29].

These corollaries consider each factor separately, but these factors often influence each other. For example, investigators working in fields where true effect sizes are perceived to be small may be more likely to perform large studies than investigators working in fields where true effect sizes are perceived to be large. Or prejudice may prevail in a hot scientific field, further undermining the predictive value of its research findings. Highly prejudiced stakeholders may even create a barrier that aborts efforts at obtaining and disseminating opposing results. Conversely, the fact that a field is hot or has strong invested interests may sometimes promote larger studies and improved standards of research, enhancing the predictive value of its research findings. Or massive discovery-oriented testing may result in such a large yield of significant relationships that investigators have enough to report and search further and thus refrain from data dredging and manipulation.

Most Research Findings Are False for Most Research Designs and for Most Fields

In the described framework, a PPV exceeding 50% is quite difficult to get. Table 4 provides the results of simulations using the formulas developed for the influence of power, ratio of true to non-true relationships, and bias, for various types of situations that may be characteristic of specific study designs and settings. A finding from a well-conducted, adequately powered randomized controlled trial starting with a 50% pre-study chance that the intervention is effective is eventually true about 85% of the time. A fairly similar performance is expected of a confirmatory meta-analysis of good-quality randomized trials: potential bias probably increases, but power and pre-test chances are higher compared to a single randomized trial. Conversely, a meta-analytic finding from inconclusive studies where pooling is used to “correct” the low power of single studies, is probably false if R ≤ 1:3. Research findings from underpowered, early-phase clinical trials would be true about one in four times, or even less frequently if bias is present. Epidemiological studies of an exploratory nature perform even worse, especially when underpowered, but even well-powered epidemiological studies may have only a one in five chance being true, if R = 1:10. Finally, in discovery-oriented research with massive testing, where tested relationships exceed true ones 1,000-fold (e.g., 30,000 genes tested, of which 30 may be the true culprits) [30,31], PPV for each claimed relationship is extremely low, even with considerable standardization of laboratory and statistical methods, outcomes, and reporting thereof to minimize bias.
Table 4. PPV of Research Findings for Various Combinations of Power (1 − β), Ratio of True to Not-True Relationships (R), and Bias (u)

Claimed Research Findings May Often Be Simply Accurate Measures of the Prevailing Bias

As shown, the majority of modern biomedical research is operating in areas with very low pre- and post-study probability for true findings. Let us suppose that in a research field there are no true findings at all to be discovered. History of science teaches us that scientific endeavor has often in the past wasted effort in fields with absolutely no yield of true scientific information, at least based on our current understanding. In such a “null field,” one would ideally expect all observed effect sizes to vary by chance around the null in the absence of bias. The extent that observed findings deviate from what is expected by chance alone would be simply a pure measure of the prevailing bias.

For example, let us suppose that no nutrients or dietary patterns are actually important determinants for the risk of developing a specific tumor. Let us also suppose that the scientific literature has examined 60 nutrients and claims all of them to be related to the risk of developing this tumor with relative risks in the range of 1.2 to 1.4 for the comparison of the upper to lower intake tertiles. Then the claimed effect sizes are simply measuring nothing else but the net bias that has been involved in the generation of this scientific literature. Claimed effect sizes are in fact the most accurate estimates of the net bias. It even follows that between “null fields,” the fields that claim stronger effects (often with accompanying claims of medical or public health importance) are simply those that have sustained the worst biases.

For fields with very low PPV, the few true relationships would not distort this overall picture much. Even if a few relationships are true, the shape of the distribution of the observed effects would still yield a clear measure of the biases involved in the field. This concept totally reverses the way we view scientific results. Traditionally, investigators have viewed large and highly significant effects with excitement, as signs of important discoveries. Too large and too highly significant effects may actually be more likely to be signs of large bias in most fields of modern research. They should lead investigators to careful critical thinking about what might have gone wrong with their data, analyses, and results.

Of course, investigators working in any field are likely to resist accepting that the whole field in which they have spent their careers is a “null field.” However, other lines of evidence, or advances in technology and experimentation, may lead eventually to the dismantling of a scientific field. Obtaining measures of the net bias in one field may also be useful for obtaining insight into what might be the range of bias operating in other fields where similar analytical methods, technologies, and conflicts may be operating.

How Can We Improve the Situation?

Is it unavoidable that most research findings are false, or can we improve the situation? A major problem is that it is impossible to know with 100% certainty what the truth is in any research question. In this regard, the pure “gold” standard is unattainable. However, there are several approaches to improve the post-study probability.

Better powered evidence, e.g., large studies or low-bias meta-analyses, may help, as it comes closer to the unknown “gold” standard. However, large studies may still have biases and these should be acknowledged and avoided. Moreover, large-scale evidence is impossible to obtain for all of the millions and trillions of research questions posed in current research. Large-scale evidence should be targeted for research questions where the pre-study probability is already considerably high, so that a significant research finding will lead to a post-test probability that would be considered quite definitive. Large-scale evidence is also particularly indicated when it can test major concepts rather than narrow, specific questions. A negative finding can then refute not only a specific proposed claim, but a whole field or considerable portion thereof. Selecting the performance of large-scale studies based on narrow-minded criteria, such as the marketing promotion of a specific drug, is largely wasted research. Moreover, one should be cautious that extremely large studies may be more likely to find a formally statistical significant difference for a trivial effect that is not really meaningfully different from the null [32–34].

Second, most research questions are addressed by many teams, and it is misleading to emphasize the statistically significant findings of any single team. What matters is the totality of the evidence. Diminishing bias through enhanced research standards and curtailing of prejudices may also help. However, this may require a change in scientific mentality that might be difficult to achieve. In some research designs, efforts may also be more successful with upfront registration of studies, e.g., randomized trials [35]. Registration would pose a challenge for hypothesis-generating research. Some kind of registration or networking of data collections or investigators within fields may be more feasible than registration of each and every hypothesis-generating experiment. Regardless, even if we do not see a great deal of progress with registration of studies in other fields, the principles of developing and adhering to a protocol could be more widely borrowed from randomized controlled trials.

Finally, instead of chasing statistical significance, we should improve our understanding of the range of R values—the pre-study odds—where research efforts operate [10]. Before running an experiment, investigators should consider what they believe the chances are that they are testing a true rather than a non-true relationship. Speculated high R values may sometimes then be ascertained. As described above, whenever ethically acceptable, large studies with minimal bias should be performed on research findings that are considered relatively established, to see how often they are indeed confirmed. I suspect several established “classics” will fail the test [36].

Nevertheless, most new discoveries will continue to stem from hypothesis-generating research with low or very low pre-study odds. We should then acknowledge that statistical significance testing in the report of a single study gives only a partial picture, without knowing how much testing has been done outside the report and in the relevant field at large. Despite a large statistical literature for multiple testing corrections [37], usually it is impossible to decipher how much data dredging by the reporting authors or other research teams has preceded a reported research finding. Even if determining this were feasible, this would not inform us about the pre-study odds. Thus, it is unavoidable that one should make approximate assumptions on how many relationships are expected to be true among those probed across the relevant research fields and research designs. The wider field may yield some guidance for estimating this probability for the isolated research project. Experiences from biases detected in other neighboring fields would also be useful to draw upon. Even though these assumptions would be considerably subjective, they would still be very useful in interpreting research claims and putting them in context.

Box 1. An Example: Science at Low Pre-Study Odds

Let us assume that a team of investigators performs a whole genome association study to test whether any of 100,000 gene polymorphisms are associated with susceptibility to schizophrenia. Based on what we know about the extent of heritability of the disease, it is reasonable to expect that probably around ten gene polymorphisms among those tested would be truly associated with schizophrenia, with relatively similar odds ratios around 1.3 for the ten or so polymorphisms and with a fairly similar power to identify any of them. Then R = 10/100,000 = 10−4, and the pre-study probability for any polymorphism to be associated with schizophrenia is also R/(R + 1) = 10−4. Let us also suppose that the study has 60% power to find an association with an odds ratio of 1.3 at α = 0.05. Then it can be estimated that if a statistically significant association is found with the p-value barely crossing the 0.05 threshold, the post-study probability that this is true increases about 12-fold compared with the pre-study probability, but it is still only 12 × 10−4.

Now let us suppose that the investigators manipulate their design, analyses, and reporting so as to make more relationships cross the p = 0.05 threshold even though this would not have been crossed with a perfectly adhered to design and analysis and with perfect comprehensive reporting of the results, strictly according to the original study plan. Such manipulation could be done, for example, with serendipitous inclusion or exclusion of certain patients or controls, post hoc subgroup analyses, investigation of genetic contrasts that were not originally specified, changes in the disease or control definitions, and various combinations of selective or distorted reporting of the results. Commercially available “data mining” packages actually are proud of their ability to yield statistically significant results through data dredging. In the presence of bias with u = 0.10, the post-study probability that a research finding is true is only 4.4 × 10−4. Furthermore, even in the absence of any bias, when ten independent research teams perform similar experiments around the world, if one of them finds a formally statistically significant association, the probability that the research finding is true is only 1.5 × 10−4, hardly any higher than the probability we had before any of this extensive research was undertaken!

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How Fauci solved AIDS

September 19th, 2007

At AIDS panel, future Nobelist Fauci revealed way forward

Add HIV to boost T-cells, eliminate drugs

Long run danger remedied by normal health measures

fauci-white-coat.pngAs we were saying, we welcome the Lasker prize which Dr Anthony Fauci of NIAID has won, because we already recognized a year ago the extraordinary contribution that the well tailored director of the National Institute of Allergies and Infectious Diseases had earlier made quietly to the final solution of the world wide AIDS panic, at a New School panel in June last year.

For some reason, perhaps personal modesty, Dr Fauci had not informed the general public previously of his breakthrough in understanding, but merely communicated it to the Proceedings of the National Academy and included it in a chapter on the Immunology of AIDS he wrote for the textbook “Fundamental Immunology”, edited by William E. Paul MD and published by Lippincott, Williams and Wilkins in 2003 (p. 1295):

What Fauci confirmed to the few graduate students and working scientists who perused this book was that the result of HIV arriving in the human body was to touch off and maintain proliferation of T-cells, rather than killing them off.

What happens is that for a 56 fold (5600 per cent) gain in HIV early on CD4 T-cells drop maybe 6% but CD8 T-cells rise 20 per cent. The net increase is there until drugs are provided, in which case this beneficial effect is wiped out. If the drugs are stopped, then the benefit is once again felt.

The total outcome is hidden in the complexity of the immune system – there are other major factors involved in the standard and rather misleading T-cell count, such as rate of production, redistribution, longevity of cells, level of apoptosis and activation induced cell death – but these trends are clear, Fauci pointed out:

“Several investigators have demonstrated that there is an increase in CD4+ T-cell proliferation in both HIV and SIV infection. In certain studies, the enhanced T-cell proliferation that was observed during active disease was significantly decreased following the initiation of anti-retroviral therapy, and proliferation increased again in parallel with plasma viremia following the cessation of treatment in these individuals.

Read the Proceedings for genuine AIDS truths

Fauci’s reference is a paper by Lempicki R. A. et al. in the Proceedings of the National Academy of Sciences (97:13778-83, 2000). The Proceedings is the place where all those seriously interested in what is really going on in science should go, perhaps. It is after all, the place where Peter Duesberg’s definitive review and rejection of HIV as the cause of AIDS took place nearly two decades ago, a beautifully written and argued exposition with 200 footnoted references from mainstream literature which oddly enough has never been answered in the same journal, though the HIV=AIDS paradigm author Bob Gallo promised the editors he would do so.

Apparently Gallo preferred to do so from the safe bunker of the last chapters of Virus Hunting, his 1991 book three years later which was happily not subject to peer review, nor did it have to provide references, unlike Duesberg’s masterpiece, which was afterwards cited in Nobel prize winning biologist Walter Gilbert’s graduate class at Harvard as an exemplary paradigm challenge. But we digress, as usual for the benefit of newcomers to this issue.

Fauci explains what kills T cells

faucihairflat.jpgReturning to Dr Fauci’s brave and perspicacious statement drawing the attention of insiders to the efficacy of HIV in stimulating the immune system, and the negative impact of drugs, this seemed at such odds with the general assumption in HIV∫AIDS that HIV kills T-cells rather than adds to them, and that drugs are needed to defeat the virus at whatever cost, that when Dr Fauci and Mathilde Krim mounted the stage at the New School with Larry Kramer to celebrate 25 years of HIV∫AIDS a year ago June 19th, Robert Houston took the opportunity to ask Dr Fauci about it.

The question came as a rowdy audience of middle aged gays calmed down after upsetting Larry Kramer so much with their objections to him telling the representative of the New York Times that the Times didn’t cover the issue of HIV∫AIDS enough that he stalked off the stage.

His departure was a pity, for his long time friend Dr Fauci gave an extremely informative reply which heralded the final solution of the AIDS puzzle, suggesting both its cause and its cure.

Fauci’s Final Solution in AIDS

facuimikehand-upo.jpgHere’s how it went. Houston asked his question as follows, both flattering the two exceptional scientists and armed with the reference to the Fauci written statement if for some reason the great man saw fit to deny it.

Houston: We have two of the most distinguished scientists in the world on AIDS on this panel and I would like to ask a basic scientific question. How does HIV cause AIDS? Does it do so by directly killing T-cells, as the New York Times science writers seem to tell us, or do you think it does it in the opposite way: by causing T-cells to multiply – and by overactivating the immune system?

And this is how Dr Fauci explained how HIV boosted the immune system, rather than crippled it, having identified drugs as the real cause of T-cell decline in his written review earlier:

Fauci: Well… It does it in both ways. I don’t want to waffle with you on that but it is very, very clear that HIV is related to a very aberrant turning on and activation of T-cells. When T-cells are sustained in their activation – because every time anybody in this room gets an immune response to a benign virus or bacteria your immune system activates (he draws line going up in air with his hand) and then it goes down again (draws line in the air going down again) to the base line.

We like the Freudian slip here in calling HIV a ‘benign” virus, but we may have misheard Fauci – readers can check for themselves when we put the video up on YouTube shortly for the admiration of all.

Here Fauci has confirmed that when HIV is responded to by the immune system, the T-cells are activated to drive it out, and indeed, reference to the Lempicki paper will, as Robert Houston has shown here in the last comment attached to our earlier post nominating Fauci for the Nobel, for a 56-fold rise in HIV viral load between early and intermediate levels of infection, CD4 T-cells decline not very much (around 6% in the chart), while CD8 T-cells rise 20 per cent, for a combined rise of 11%. Now Fauci continued:

When you have a high level of viremia with a lot of activation you just drive the immune system to an aberrant form of activation that leads to the death of a cell, even cells which don’t directly get infected with HIV. They die by a process called apoptosis, meaning essentially they die a suicidal type death.

Here the director of NIAID for 23 years is bringing in cell suicide as a means of explaining how T-cells do die in the face of HIV. Apoptosis is indeed the last refuge of HIV∫AIDS paradigm promoters in their anxiety to explain how it is that HIV might be causing immune collapse by killing T-cells, when there is no discernible biological activity along these lines detected by any researcher in the 23 years of exceptionally well funded HIV∫AIDS research.

The problem is that until Dr Fauci in this reply confirmed that this was the case, doubters had wondered what the evidence was that there was any more cell suicide than normal when the body is aiming for homeostasis, ie returning to the normal balance in the proportions of the constituents of the blood. Cell suicide is a normal process here, and with the levels being maintained, as Dr Fauci confirms, it is hard to see how it is killing off so many T-cells that the immune system collapses.

claudius-ptolemy.jpgThe difficulty that conjuring up cell suicide is intended to solve is that there is no evidence of any mechanism by which HIV directly kills T-cells, which was the original premise of Robert Gallo’s theory that HIV was the cause of the immune collapse of AIDS. The evidence is that HIV does not kill T-Cells, so enthusiasts for the well funded paradigm had to come up with indirect ways it might get rid of T-cells.

Apoptosis is the best they could come up with, which didn’t present any great difficulty to the army of officials, politicians, activists, health workers, journeyman scientists and dying AIDS patients who were told of this solution perhaps because none of them had heard of Ptolemy the Egyptian, who managed to work out elliptical orbits that could predict the movements of the planets even though he assumed that the Sun went around the Earth, rather than vice versa. The indirect mechanisms by which HIV is said to work its fatal effects on T-cells are the elliptical trajectories of the HIV∫AIDS explanation of AIDS.

Now, however, the director of NIAID sums it all up in one beautiful breakthrough concept which accounts, finally, for the ultimate decline and fall of the human immune system after years of responding to HIV by making T-cells which effectively drive out the virus in a matter of weeks, reducing it to minimal levels of as little as one to five active virions per milliliter, impossible to detect without PCR.

Why does it all change? Steam is key

pcousyn-steam_engine.jpgThe puzzle has always been, why does the immune system collapse in five ten or even twenty years, if it has got rid of virtually all virus within six weeks. Fauci now ‘explains’:

You can wind up depleting your T-cells by direct infection and those cells dying or just a burst of aberrant activation and also some elimination by the immune system of infected cells. So it’s not a unified concept; there’s multifactorial ways in which you drain your T-cells and then after a few years you just run out of steam.

sink.jpegIn other words, Dr Fauci is prepared to throw everything including the kitchen sink into the mix. Those who say that HIV doesn’t kill T-cells are wrong, it does kill them by “direct infection” somehow. Then you have more killed by cell suicide after a “burst of aberrant activation”. Finally – here is the key at last – the immune system just “runs out of steam”.

Dr Fauci’s Solution to AIDS

Robert Houston confesses that he failed to follow up his question because he was prepared only for Fauci to deny that T-cells proliferated when faced with HIV. What we wish he had done is congratulate Fauci for a conceptual framework which tells us how to defeat AIDS.
Unless we misunderstand him, here is his solution to HIV∫AIDS:

1. With even a dramatic leap in viral load, the T-cells divide faster in response. The end result is that CD 8 T-cell count goes up substantially, with no significant decline in CD 4 T-cell count.

2. So if there is any concern that the immune system is weak, simply add more HIV.

3. Remove ARV drugs, and T-cells will multiply and return to excess levels again.

4. After defeating HIV is a matter of weeks and then maintaining this success for up to twenty years, somehow the immune system might run of steam.

5. But as Dr Fauci’s choice of phrase implies this loss of steam can surely be prevented with proper exercise, nutrition, fresh air, travel and all other general health stimulants, including the renewed optimism that comes from knowing there is a solution – the Fauci Solution to AIDS.

But since the Lasker winner didn’t actually mention this last point explicitly perhaps we can check with him at the lunch where he will accept his prize, surrounded by the members of the medical and economic establishment, of which he has long been a fully paid up member.

faucihandsinair.jpgSo after years of the whole world left confused and supporting antiretroviral drugs as the only defense against the deadly effect of HIV, we have Dr Fauci to thank for telling us that on the contrary, it is HIV rather than drugs which benefit the immune system.

Of course, it must be acknowledged that both Robert Gallo, and two years later Peter Duesberg, were the first to point out that HIV was harmlessly involved in AIDS. But neither of them detected the fact that it was actually beneficial to AIDS patients.

Gallo, of course, proved that HIV was not the cause of AIDS with his 1984 papers showing it was occurring in only one third of sick AIDS patients, with pre-AIDS patients having it more often, suggesting it was a possible antidote. Now Anthony Fauci has found why – HIV stimulates the immune system – and he has also noticed that drugs have a negative impact.

Considering that the drug companies involved in HIV∫AIDS have a considerable interest in this revision of the paradigm, we feel that Anthony Fauci is showing considerable moral fortitude in revealing these insights in public in front of gay activists, who were already a noisy crowd and most of them funded by the drug companies.

Luckily, however, none of them noticed.

John P. Moore Brings Down The AIDS Paradigm (Part 2)

May 30th, 2007

Moore redeems himself by helping Duesberg destroy crux of HIV∫AIDS theory

Scores studies for ignoring obvious: HIV acts as vaccine against itself

John Moore, quiet Truthteller

samsonbigmaybe.jpgAs we were saying, the other day we made a remarkable discovery in the scientific literature of HIV∫AIDS.

John Moore, it turns out, has justified our obstinate faith in his exemplary character as a scientist in one of our most distinguished medical institutions by publishing a paper which finds the heart of the paradigm empty, and its claims of a virus overcoming the resistance of the body provably void.

Moore as paradigm assassin

To put it bluntly, John P. Moore Ph.D. has written a paper which tears out the thumping heart of his entire campaign in defense of the beleaguered paradigm and throws it to the paradigm attack dogs he is usually occupied with trying to kick as hard as he possibly can.

The title of this quietly seminal work is a question: “Is there enough gp120 in the body fluids of HIV-1 infected individuals to have biologically significant effects?”

The minireview can be found in Virology, 323 (2004) pp1-8, and is written with P. J. Klasse, who is also at the Department of Microbiology and Immunology, Weill Medical College of Cornell University, 1300 York Avenue, W-805, New York NY 10021 (Fax 212 746 8340 jpm2003@med.cornell.edu).

Gp120 is the envelope glycoprotein of the vaunted Human Immunodeficiency Virus, which Moore in public is strenuous in insisting is the valid root cause of the statistically burgeoning AIDS pandemic reported by the New York Times and the Council of Foreign Relations and other very established sources of public advice to be spreading around the world and threatening the security of almost every nation.

Private science

Apparently he is not saying the same thing off stage, however. It seems the paper was a review more or less intended for the private reading of the HIV virologist’s club, and not for the general public or even the edification of journalists and science writers.

This double think is standard behavior for the well funded members of the HIV∫AIDS elite. They profess one thing in public, and like to carry on their real discussion behind the scenes, talking more realistically among themselves about their stock in trade, the belief that HIV somehow causes AIDS, and wondering aloud how it could possibly be reconciled with the stream of contradictory studies pouring forth very year, without unsympathetic interlopers present who might notice the dissonance between public confidence and private admissions about the missing heart of the paradigm.

Secretly supporting the HIV critics

For the admissions of Moore’s paper in the course of its review and conclusion are of exactly that kind. They unmistakably deny the possibility that HIV will have any significant effect on the body after antibodies clear it from the bloodstream, for the simple reason that there just isn’t enough left in the blood to have any biological effect. That is the answer to the question in his title that Moore himself gives. In doing so, he removes the essential prop of the entire HIV∫AIDS system.

Moore himself thus stands revealed as the HIV∫AIDS dissidents best friend, a man who from the heart of the establishment has had the courage to state that the emperor paradigm has no clothes. Moore, in fact, turns out to be a second Duesberg.

This is a very brave man, a man whose urge to investigate, find and announce the truth cannot be gainsayed by considerations of affiliation or funding, or even having, in the form of a notorious Op Ed piece, taken a firm stand for falsity in the pages of the New York Times.

Moore, the new Duesberg?

However, we realize that few readers are going to take this from us on faith, after all Moore has put the dissidents through, including even trying to attack their jobs through phoning up their employers. So we are happy to give chapter and verse, from this paper and a couple of others.

What we will reveal will suggest to the historians among us that when Duesberg gets his combined double Nobel for the solution to AIDS and for peace, it is not impossible that standing beside him proudly will be the once perfidious Moore, newly revealed here as the savior of AIDS patients from mismedication and deliverer of the world from the lethal infection of the AIDS meme.

Uprooting the foundation

So let’s see what the paper says. First of all, in this pathbreaking Virology review, Moore debunks the papers over the past decade in which gp 120, the surface envelope glycoprotein of HIV-1, has been added to cells in vitro, ie to human T cells in a lab dish, on the false assumption that this mimics the effect of gp120 in the live bloodstream. He writes that

“the outcome is generally that gp120 can kill a target cell or perturb its normal functions, and it is assumed that what is observed in vitro [in the lab] is relevant in vivo [in the body].”

The purpose of Moore’s review, in fact, is to see whether this is correct or not. Is there enough gp120 in the blood in vivo to do anything? Or are HIV researchers overlooking the effects of antibodies, which may block the effects seen in the lab dish and prevent them from occurring in the body?

Since this is the function of antibodies, all present may already feel they know the answer, which is Yes, HIV lab researchers evaluating the effect of gp120 have been overlooking the effects of protective antibodies in the live bloodstream.

Antibodies defeat HIV

Seventeen years after Peter Duesberg said the same thing, this indeed is the answer that Moore will arrive at. In the living patient antibodies defeat HIV and clear it from the blood stream so effectively that it can have no effect on T cells or anything else. End of story. HIV is not a lethal invader of the body biological, it is quickly seen off by the immune system of a healthy person.

“Our intent is to question whether such an extrapolation is reasonable on quantitative grounds, particularly when the presence of antibodies (Abs) in the plasma of HIV-1-infected persons is taken into account.”

Overestimates of gp120 in the blood

Moore first cites a bunch of studies to show the range of gp120 concentrations used in experiments, which have varied from 1pM to 1uM. Naturally some of these have found toxic effects, since if you add enough of anything to a culture you’ll get a toxic effect, and contamination with bacteria is common in labs, yielding endotoxins from their walls. But the problem here, he says, is that the papers everyone has relied on for the past decade or more overestimate the amount of gp120 in the blood of HIV+ people.

“Two papers are usually cited to suggest that gp120 concentrations used in vitro resemble those in bodily fluids, specifically plasma… Our impression is that these papers are often either cited incorrectly or misunderstood.”

He goes into more detail, which we will hide from those uninterested in the details.

The papers are Gilbert et al, (Enzyme-linked immunoassay for human immunodeficiency virus type 1 envelope glycoprotein 120, in the Journal of Clinical Microbiology, 29 (1), pp 142-147) 1991, and Oh et al (Identification of HIV-1 envelope glycoprotein in the serum of AIDS and ARC patients, in the Journal of AIDS 5 (3) , pp 251-256) 1992. Both are rejected by Moore as misleading, and he looks more favorably in a later paper, Gilbert et al, 2003 (Long term safety analysis of preventive HIV-1 vaccine evaluated in AIDS vaccine evaluation group NIAID-sponsored Phase 1 and Phase 2 clinical trials, Vaccine 21 (21-22), 2933-2947).

“Oh et al detected gp120 in a majority of AIDS patients’ sera in the range 0.1-0.8 nM. No gp120 was found in the sera of HIV-1 infected individuals with AIDS related complex (ARC). Thus, only in sera from people at the late clinical stages of infection, when HIV-1 antigen levels tend to rise, was free gp120 ever, apparently, detectable. However, gp120 in complex with antibody (Ab) was found in a larger proportion of sera, a point to which we shall return.”

Translation: Oh’s finding is that only when people got really sick and their immune system was having trouble coping was any free viral envelope protein detectable floating around in the bloodstream.

Otherwise, the viral envelope protein was only detected with antibodies attached, indicating as other studies have shown that the immune system does such a good job knocking out HIV with antibodies that there isn’t a detectable level in an AIDS patient’s bloodstream until they fall really ill, when the immune system is crippled and lets some HIV run loose for lack of antibodies.

Interestingly, this is going to be Moore’s final message, though he actually rejects the findings of this paper by Oh. Our interpretation of his conclusion might be phrased as follows, though we are not giving you an actual Moore quotation: In general, a healthy immune system knocks out HIV and its proteins, period, and there is no need for any vaccine, thank you very much. Yours truly, John Moore.

In his corrective review Moore then compares the Gilbert study of 2003, a different paper from a different Gilbert, where gp120 was detected only in the range 2-20 pM, and only in a minority of AIDS and ARC patients who were p24 antigenemic, ie with concentrations one to two orders of magnitude lower than the Oh study. The two studies (Oh 1991 and Gilbert 2003) do not agree with each other, therefore, and shouldn’t be cited as if they did, he says:

In contrast, Gilbert et al. (2003) detected gp120 only in the range 2–20 pM, and then only in a minority of sera from p24-antigenemic AIDS and ARC patients. The plasma gp120 concentrations detected by Oh et al. were thus one to two orders of magnitude higher than those described by Gilbert et al. (2003). Hence, the two papers should not be cited as agreeing with each other.

He then describes the methods used in each to see why the difference, and in a confused discussion finds that Oh used a method which is “questionable at best” in its ability to detect and quantify gp120 in plasma, and undoubtedly the later Gilbert study is right to lower the estimate of gp120 concentration in the bloodstream. He concludes a slew of papers have been written by the HIV∫AIDS club based on erroneous assumptions that over estimate gp120 concentrations in plasma, especially when the level of viremia is considered (even at high levels, eg a million per milliliter, the protein is hardly found – it’s 2-4 orders of magnitude lower ie 100 to 10,000 times lower than the claimed levels used in experiments).

Moore confesses – he found it first and failed to publish!

Moore moves on to discuss the level of viremia in plasma and what does he have to say? Why, that Gilbert et al.(2003) had tried mixing gp120 with human serum only to find it significantly reduced the gp120 signal and that if you add a lot of HIV positive blood, the gp120 is entirely knocked out by the antibodies in the plasma!

Not only Gilbert, moreover, has found this. Moore himself now confesses he observed the same effect many years ago in experiments which he never published!

Why didn’t Moore publish sooner?

In other words, Moore found many years ago that human antibodies thoroughly stymied the virus by attaching to the free viral envelope gp120, and thus no doubt to the virions, and somehow failed to publish this finding! Could it be that he was not anxious to spoil the global vaccine initiative led by his long time pal and sponsor David Ho, and tactfully restrained himself from putting into print what would have stymied Ho by showing there was no need for a vaccine against HIV at all, since it vaccinated against itself very well. Surely not?

Surely there must have been some less political motive for Moore’s odd lack of publication of this stupendous result, which would have raised the curtain of fear from around the Virus to demonstrate that it was rendered powerless by the natural responses of any healthy person?

The many millions that would have escaped the shame, despair, fear of death and prison, and the general self deteriorating panic that overcame them on hearing they were under a death sentence from an undetectable virus, one that eventually works its deadly magic in a way as yet unknown to science to bring them down with ghastly internal and external rot and speed them into the grave after a lull of apparently healthy life of ten or twenty years or more from the time of infection, these millions might wish he had spoken up earlier on a more prominent stage.

But they can at least be grateful to John P. Moore for at last if rather belatedly publicizing to the few readers of this obscure Virology paper his watershed finding, which fits so well the analysis of Peter Duesberg seventeen years earlier which pointed out exactly the same thing, since it was by then already demonstrated in the literature that no one was bothering to read any more.

But since Duesberg’s papers have proved to be apparently too difficult to read and respond to by his peers such as Robert Gallo, Anthony Fauci, and David Baltimore, who are far too busy saving lives, it apparently took a minor officer of the paradigm propaganda and promotion army in the service of HIV to come right out and say it, and confirm Duesberg’s point, after 17 years.

Here’s the beef

Anyone who doubts what we have to say must read it for themselves, of course. So here is the following paragraph of John P. “Truthteller” Moore’s breakthrough review, which can now be compared to those of Peter Duesberg if not in literary quality or analytical cogency at least in its power to affect events, for this is what the world has been waiting for, confirmation from the HIV paradigm A team that HIV (all its interactions depend on this protein, gp120) is defeated by human antibodies, and there is no need for the billion dollar global vaccine effort which has so far resulted in more than twenty ineffectual stabs at producing a vaccine to engender antibodies to defeat HIV, antibodies which HIV itself does very well at exciting all by itself, to a level that already utterly defeats its supposed depredations because the HIV is entirely neutralized and reduced to a harmless level in the blood which is undetectable without PCR, which is the only way the negligible and biologically irrelevant quantities of the viral sequence in human blood can be magnified geometrically into something significant and detectable.

Here it is, the paragraph which makes history, and in our opinion places John Moore one step closer to a Nobel side by side with Peter Duesberg for having the public spirit, the guts and the undeniable truthtelling urge to inform the world of the reality of the harmlessness of HIV, whatever the dispproval, scorn, calumny and rejection which may now be heaped upon his irremediably scientific head by David Ho, Bob Gallo, Anthony Fauci, and David Baltimore, the nobles of the court of HIV∫AIDS, where the Emperor HIV is now revealed to have no clothes of pathogenicity at all.

A related issue, approached by Oh et al and addressed more directly by Gilbert et al (2003) is that of interference by plasma antibodies. Gilbert et al (2003) found that mixing gp120 with control human serum significantly decreased the subsequent signal and that high titers of HIV-1+ sera could abrogate the signal completely. One of us (J.P.M.) observed much the same effect in unpublished experiments many years ago, using a capture enzyme immunoassay based on Ab D7324 and a polyclonal anti-gp120 serum. Thus, when a known amount of gp120 was spiked into different HIV-1+ sera, the anti-gp120 Abs present interfered significantly with gp120 detection, and to an extent that varied greatly between the sera. Indeed, it was impossible to judge from the assay readout what amount of gp120 had been added to the different HIV-1+ sera. Therefore, any estimation of how much gp120 was naturally present in the HIV-1+ sera was clearly problematic. The same concerns apply to p24 antigen quantification in the presence of plasma anti-p24 antibodies: only when immune complexes are dissociated, for example by the use of heat, can p24 concentrations be properly determined (Schupbach and Boni, 1993).(Emphasis added.)

Translation: Mixing human HIV+ blood with viral envelope gp120 results in its complete effective eradication by the HIV antibodies in the serum, So if you expect to measure the level of gp120 in the blood of a healthy human, don’t bother. Same applies to p24, another component of HIV and an antigen that antibodies also neutralize out of sight. All you will get to measure is antibodies (Abs).

Which is precisely what “AIDS tests”, tests for HIV, actually measure – antibodies! Surprise!

Moore’s inner tension

An even bigger surprise is that the estimable Moore cannot resist fessing up he found this out years ago by experimenting and failed to alert the public and other scientists to his discovery by publishing his result.

Clearly the pressures against this exemplary truthteller must have been immense to prevent this innately high integrity scientist from doing his duty in this regard, and so we redouble our praise for his giving in to the impulse at long last. What measure of pyschological inner conflict was playing out in Moore’s combative psyche during this process we cannot gauge, but we do know that the decision to go public cannot have been undertaken lightly.

A Samson of whistleblowers

For here Moore is undermining the chief pillar of the paradigm he has so vociferously supported in the last couple of years. He is in effect a whistleblower in the game in which he has been a chief player. Among whistleblowers he is now joining the exalted ranks of whistleblowers who have changed history.

He is in fact a Samson of whistleblowers, whose muscular arms have been wrapped around the biggest and thickest pillar of the temple of HIV∫AIDS, and with a final heave has uprooted it from the marble floor and tossed its broken halves away from him as the entire edifice has come apart above him, threatening to kill him at the same time as the horrified high priests whose armed guard he has recently commanded.

Why Moore went ballistic

Of course it appears that having let this tiger sized cat out of the bag in the narrow confines of a journal read only by the HIV club Moore seems to have chickened out, abandoned his new policy of public acknowledgement of real science and conducted ever more fierce attacks on HIV critics in his Times Op Ed piece, his AIDSTruth.org site and in email warfare with Harvey Bialy. Could it be that Fauci et al made it perfectly clear that he had gone too far? Surely not. After all, the AIDS generals have never been very keen on discussing the reality behind HIV and AIDS science in public themselves, so why should they encourage Moore to be so loud in his denials?

We conclude that it must have been the torment of having his brief moment in the fresh air of honest science curtailed that twisted Moore into some kind of psychological pretzel of inner conflict, and led to his recent ungentlemanly conduct in making excessive remarks even including the humble host of this untrumpeted blog, using such undignified words as “slime” and so forth.

Only the torment of inner conflict can account for this unexpected phase of Moore’s fine career, in which he has temporarily left behind the civility inculcated into his combative character by Downing, his respectable Cambridge college.

We want to encourage him to choose the Dr Jekyll side of his recently Mr Hyde character by supporting him completely in pursuing his 2004 path of honest admission in every way we can. We would encourage him by noting that Robert Gallo confirmed what he has said in his testimony to the Adelaide court which helped block the appeal of Parenzee against his jail sentence (see earlier posts). Gallo admitted that HIV was ineffectual against antibodies in a normal healthy person. But then so did Robin Weiss, the British equivalent of Robert Gallo, back in 1985 (R. A. Weiss et al, Neutralization of HTLV-III by sera of AIDS and AIDS-risk patients, Nature 316:69-72, 1985). Of course, the party line since then has been that HIV mutates too fast for antibodies to keep up. Not true, according to at least one mainstream paper which finds that the body’s antibodies keep up very well with HIV’s mutant escapism (D. D. Richman et al. Rapid evolution of the neutralizing antibody response to HIV type 1 infection. Proc. Nat. Ac. Sci.100:4144-4149, 2003.

Nails in the HIV coffin lid

Moore makes other confirming points in the article, just in case anyone thinks we are quoting selectively and giving a false impression. Here are the main ones:

The methods that have been used to date are not any use in estimating how much gp120 there is in the blood of HIV+ people:

Taken together, the uncertainty about the efficiency of gp120 capture, the extent of cross-reactivity of the detecting Abs with any gp120 present in plasma (at least in the assay used in Oh et al), and the interference by plasma anti-gp120 Abs, all but preclude any accurate estimate of plasma gp120 concentrations by the methods that have been used to date….The limitations of the published assays need to be taken into account when these papers are cited (Gilbert et al 2003 and Oh et al).

His guess is that these papers probably overestimated gp120 levels in plasma in vivo by two to four orders of magnitude (100x-10,000x).

It can be calculated that a plasma viral load of 10^6 virions/ml – a high level for chronic HIV-1 infection – corresponds to only 0.03-0.07 pM of virion associated gp120 and 2-3 pM p24. While this concntration of virion-associated p24 is somewhat below the upper range of p24 of total p24 in plasma (Ledergerber et al 2000) this gp120 concentration is between two (Gilbert et al, 1991) and four (Oh et al, 1992) orders of magnitude lower than the often cited values.

For, as he has already noted, the plasma antibodies neutralize most of the gp120:

We noted above that plasma anti-gp120 Abs mask the detection and quantification of gp120. The same antibodies have a very significant effect on the receptor interactions of any gp120 that is present in plasma. Abs to gp120 are usually present at high enough concentrations in plasma to bind up most of the gp120 present.

The antibodies in plasma are sufficient to prevent pretty much all binding of gp120 to CD4 or the co-receptors:


Thus, in the presence of undiluted HIV-1+ plasma, as occurs in vivo, there would be effectively no binding of gp120 monomers to CD4 or the co-receptors. This is rarely accounted for in the design and interpretation of in vitro studies with recombinant gp120, but it always should be.

Moore goes on to say that perhaps antibodies would be less effective on gp120 hiding in the central nervous system or other tissue locales, where they are present only at low levels. There is no way of telling what the outcome might be, he says. But it seems plausible that gp120 could be present in places other than the blood at much higher concentrations than in the plasma, for example, the interstitial spaces in lymph nodes. Such possibilities are hard to imitate in experiments, so he is forced to “conclude that the relevant gp120 concentrations are essentially unknown.”

The bottom line

The bottom line is that the levels of gp120 present in plasma in vivo “are far below” the levels where they have significant effects on cells in vitro ie in the lab. And any experiments must take into account the effects of antibodies which are present in vivo.

As noted above, HIV-1 positive serum antibodies will have much the same effect as the specific MAbs (monoclonal antibodies), and their presence in vivo must be taken into account.

Oops! Moore tries to cloak his realism

Having reached this rather startling set of conclusions, amounting to an admission that the paradigm “HIV causes AIDS” is a non starter given the power of human antibodies.to wipe out the virus in the blood, and its proteins, Moore then does a pretty dance to salvage his respectability with his HIV∫AIDS cohorts before he is cast into as deep a dungeon as Peter Duesberg for giving wrong answers to the scientific Inquisition.

We do not argue that gp120 could never have a biological effect on cells in vivo via receptor-mediated interactions. Nor is it impossible that virions could influence cellular processes in vivo independently of receptor-mediated fusion events.

We do, however, argue that it is not an adequate mimic of in vivo biology simply to add free gp120 (or virions) to target cells in vitro in amounts that are apparently several orders of magnitude greater than in body fluids…(The two decade-old) papers are not consistent with each other, and the more frequently cited study, by Oh et al, has serious design flaws that may cast doubt on the gp120 concentrations it promulgates. The much lower gp120 concentrations recorded by Gilbert et al (2003) are likely to be closer to true levels. And the presence of plasma anti-gp120 Abs that block receptor binding should inform the design of in vitro experiments…. Some of these considerations apply, of course, to other studies of similar design that use high concentrations of other HIV-1 proteins, such as Tat and Vpr, in vitro, in the hope that this is relevant to pathogenesis.

Sadly, as you can see, it seems that Moore could not bring himself to deny his result for very long, and immediately stated it again, just to clinch it in the minds of all listeners.

What’s more, he broadened it to make sure that readers understood that what he was saying applied not only to the envelope protein gp120 of HIV but other major proteins and the virions themselves (virions are free floating virus outside the cell; provirus is its embodiment inside the cell DNA). Antibodies deal with all these variations, it is clear, if they are found in the bloodstream.

Gentlemen, your experiments are worthless

In other words, Come on guys, stop doing experiments trying to gauge the supposed destructive effect of HIV virions or its proteins on CD4 cells in the blood by throwing gp120 or any of the others into a dish of target cells when in the body there are antibodies which defeat HIV and its proteins before it can do anything to speak of.

Doing such experiments is rather like planning the Normandy invasion of the Second World War but leaving out the Germans. In the case of HIV this is likely to be even more misleading because in every healthy human there are enough German antibodies to repel boarders and throw the English and the Americans HIV virions and proteins back into the sea. An invasion by HIV is a D Day which rapidly turns into a Dunkirk.

Bravo! John P. “Truthteller” Moore for pointing to this long ignored truth.

Here is the paper, for reference: Is there enough gp120 in the body fluids of HIV-1-infected individuals to have biologically significant effects?

doi:10.1016/j.virol.2004.03.003

Minireview

Is there enough gp120 in the body fluids of HIV-1-infected individuals to have biologically significant effects?

P. J. Klasse and John P. Moore,
Department of Microbiology and Immunology, Weill Medical College of Cornell University, New York, USA
Received 16 January 2004; Revised 17 February 2004; accepted 2 March 2004. Available online 26 April 2004.

“Is there enough gp120 in the body fluids of HIV-1-infected individuals to have biologically significant effects?” [Virology 323 (2004) 1–8]
Virology, Volume 327, Issue 1, 15 September 2004, Pages 155-155
P.J. Klasse and John P. Moore

Over the past decade, many publications have described experiments in which the recombinant monomeric form of the gp120 surface envelope (Env) glycoprotein of human immunodeficiency virus type 1 (HIV-1) has been added to cells in vitro (Fig. 1). The ensuing cellular responses (e.g., activation of signal transduction pathways resulting in cytokine release, chemotaxis, proliferation, anergy, or apoptosis) are monitored. The outcome is generally that gp120 can kill a target cell or perturb its normal functions, and it is assumed that what is observed in vitro is relevant in vivo. Our intent is to question whether such an extrapolation is reasonable on quantitative grounds, particularly when the presence of antibodies (Abs) in the plasma of HIV-1-infected persons is taken into account. We cite only a small selection from this abundant literature, to illustrate the range of active gp120 concentrations reported.

Fig. 1. (a) The HIV-1 envelope glycoprotein (Env) complex consists of trimers of non-covalently linked heterodimers of an outer, receptor-binding moiety, gp120, anchored to a transmembrane protein gp41, which is involved in the fusion of the viral envelope with the cell membrane. The gp120 moiety is shown (left) interacting with the four-domain receptor, CD4. This binding induces a conformational change that facilitates the interaction of gp120 with a coreceptor, CCR5 for R5 virus and CXCR4 for X4 virus (right). The interactions of gp120 with CCR5 and CXCR4 are weak in the absence of CD4. (b) A monomer of gp120 is shown to undergo interactions corresponding to those in (a). This scheme is reproduced in many experiments making use of monomeric recombinant gp120. A significant degree of binding and many experimental effects are only obtained at much higher concentrations than what could realistically be present in extracellular fluids in vivo (top). A complex between gp120 and soluble CD4 is shown to interact with a coreceptor on the cell surface. In the absence of CD4, the affinity of gp120 for CCR5 or CXCR4 is low (bottom, left). Specific antibodies prevent gp120 from binding to CD4; this also precludes further, downstream contact with the coreceptor (bottom, right). The blocking effect of antibodies is likely to occur in vivo except in certain tissues where their concentration is lower, such as the central nervous system. (c) An HIV-1 virion is shown schematically. The Env trimers of heterodimers (gp120 and gp41) stud the phospholipid bilayer that surrounds the viral Gag proteins and RNA genome. The copy-number ratio of the Gag to Env in virions is 50.

In the in vitro experiments, the gp120 concentrations vary from 1 pM to 1 μM (ca. 0.12 ng/ml to 120 μg/ml, as 1 nM ≈ 0.12 μg/ml, e.g. Arthos et al., 2002; Chirmule et al., 1990; Davis et al., 1997; Esser et al., 2001; Goldman et al., 1994; Herbein et al., 1998; Hesselgesser et al., 1998; Huang et al., 2001; Kanmogne et al., 2001; Keswani et al., 2003; Kornfeld et al., 1988; Mann et al., 1987; Masci et al., 2003; Munshi et al., 2003; Oyaizu et al., 1990; Schneider-Schaulies et al., 1992; Tamma et al., 1997; Vlahakis et al., 2003; Wahl et al., 1989; Weinhold et al., 1989; Weissman et al., 1997 and Yao et al., 2001). Sometimes biological effects occur only at the higher end of the range, although particularly in neuronal cell systems lower gp120 concentrations can be active. In those systems, the primary effects may be partly on microglial cells, which are reported to amplify secondary effects on neurons (cf. Garden, 2002; Kaul and Lipton, 1999 and Keswani et al., 2003, reviewed in Kaul et al., 2001).

Historical measurements of plasma gp120 concentrations

Two papers are usually cited to suggest that the gp120 concentrations used in vitro resemble those in body fluids, specifically plasma (Gilbert et al., 1991 and Oh et al., 1992). Our impression is that these papers are often either cited incorrectly or misunderstood. What do they, in fact, report? Oh et al. detected gp120 in a majority of AIDS patients’ sera in the range 0.1–0.8 nM. No gp120 was found in the sera of HIV-1-infected individuals with AIDS-related complex (ARC). Thus, only in sera from people at the late clinical stages of infection, when HIV-1 antigen levels tend to rise, was free gp120 ever, apparently, detectable. However, gp120 in complex with antibody (Ab) was found in a larger proportion of sera, a point to which we shall return. In contrast, Gilbert et al. (2003) detected gp120 only in the range 2–20 pM, and then only in a minority of sera from p24-antigenemic AIDS and ARC patients. The plasma gp120 concentrations detected by Oh et al. were thus one to two orders of magnitude higher than those described by Gilbert et al. (2003). Hence, the two papers should not be cited as agreeing with each other.

Both papers rely on capture enzyme-immunoassays to quantify gp120. The assay of Gilbert et al. (2003) uses a soluble form of CD4, the primary receptor for gp120 (see Fig. 1), to capture gp120 onto a solid phase. The bound gp120 is then detected with a polyclonal sheep Ab raised against a peptide from the C terminus of gp120 of the T-cell line-adapted isolate IIIB. This antibody, D7324, cross-reacts strongly with gp120s from multiple HIV-1 strains, particularly within subtype B but also outside it (Moore and Jarrett, 1988 and Moore et al., 1994b). As soluble CD4 is pan-reactive with properly folded gp120s, the assay used by Gilbert et al. (2003) is relatively little affected by gp120 sequence diversity. In contrast, Oh et al. employed a polyclonal serum to gp120 of the IIIB isolate for capture, with a monoclonal Ab (MAb) to the V3 loop of IIIB gp120 as the detection reagent. Details of the specificity of the latter MAb are not provided, but it is stated “to have 10–15% cross-reactivity with other strains”. Regardless of whether this value refers to the extent of binding or the proportion of test gp120s that it reacted with, it is now well understood that the recognition of gp120 from primary viruses by IIIB-specific V3-loop MAbs is usually poor. The cross-reactivity capabilities of the assay used by Oh et al., and hence its ability to detect and quantify gp120 in plasma, is, therefore, questionable at best. This assay would be expected to underestimate plasma gp120 content by failing to recognize gp120 from the infecting strain. However, its results suggest that gp120 is present in plasma at surprisingly high concentrations, both relative to what was found by Gilbert et al. (2003) and to viremia, as discussed below.

A related issue, approached by Oh et al. and addressed more directly by Gilbert et al. (2003), is that of interference by plasma antibodies. Gilbert et al. (2003) found that mixing gp120 with control human serum significantly decreased the subsequent signal and that high titers of HIV-1+ sera could abrogate the signal completely. One of us (J.P.M.) observed much the same effect in unpublished experiments many years ago, using a capture enzyme immunoassay based on Ab D7324 and a polyclonal anti-gp120 serum. Thus, when a known amount of gp120 was spiked into different HIV-1+ sera, the anti-gp120 Abs present interfered significantly with gp120 detection, and to an extent that varied greatly between the sera. Indeed, it was impossible to judge from the assay readout what amount of gp120 had been added to the different HIV-1+ sera. Therefore, any estimation of how much gp120 was naturally present in the HIV-1+ sera was clearly problematic. The same concerns apply to p24 antigen quantification in the presence of plasma anti-p24 antibodies: only when immune complexes are dissociated, for example by the use of heat, can p24 concentrations be properly determined (Schupbach and Boni, 1993).

Taken together, the uncertainty about the efficiency of gp120 capture, the extent of cross-reactivity of the detecting Abs with any gp120 present in plasma (at least in the assay used by Oh et al.), and the interference by plasma anti-gp120 Abs, all but preclude any accurate estimate of plasma gp120 concentrations by the methods that have been used to date. Of note is that Gilbert et al. (2003) found no correlation between plasma p24 and gp120 concentrations, which may reflect differences in the extent of Ab complexing with the two antigens. The limitations of the published assays need to be taken into account when these papers are cited, particularly in respect of the high gp120 concentrations reported by Oh et al.

Alternative estimates of plasma gp120 concentrations

What concentrations of gp120 could be expected in HIV-1+ plasma? Plasma concentrations of the viral Gag protein (Fig. 1) p24 provide a useful guide. Most plasma p24 antigen is normally Ab-complexed or virion-associated. But after its release as a free protein, it is detected at concentrations <40 pM (Ledergerber et al., 2000), that is, just above the 2–20 pM reported for free gp120 by Gilbert et al. (2003). If virions were the only source, gp120 concentrations would be 40- to 60- fold lower than those of p24 (Chertova et al., 2002; Layne et al., 1992 and Zhu et al., 2003). It can be calculated that a plasma viral load of 106 virions/ml—a high level for chronic HIV-1 infection—corresponds to only 0.03–0.07 pM of virion-associated gp120 and 2–3 pM p24. While this concentration of virion-associated p24 is somewhat below the upper range of total p24 in plasma (Ledergerber et al., 2000), this gp120 concentration is between two (Gilbert et al., 1991) and four (Oh et al., 1992) orders of magnitude lower than the often cited values.

Gp120 that is not associated with virions could potentially be derived from infected cells. The envelope glycoprotein complex (Fig. 1) is produced and processed via the secretory pathway, whereas the Gag precursor is synthesized on free ribosomes in the cytoplasm. Although virions incorporate approximately 50-fold fewer Env than Gag molecules when they bud from cellular membranes (see Fig. 1c) (Chertova et al., 2002), we do not know the ratio of Gag to Env in infected cells in vivo. It could be argued that the majority of Env never exits from the secretory pathway, and that significant additional amounts of gp120 is released from dead or moribund cells as “viral debris” (Parren et al., 1997). However, some of this debris would not interact with receptors and such lysed cells would also release p24. Hence, it is hard to explain how gp120 proteins capable of receptor binding could be present at higher concentrations than p24.

The effect of plasma antibodies on gp120–receptor interactions

We noted above that plasma anti-gp120 Abs mask the detection and quantification of gp120. The same antibodies have a very significant effect on the receptor interactions of any gp120 that is present in plasma. Abs to gp120 are usually present at high enough concentrations in plasma to bind up most of the gp120 present. The ratio [Ab]/Kd determines their degree of binding to gp120, in accordance with the law of mass action (Klasse and Sattentau, 2002). Anti-gp120 Ab concentrations have been estimated to be in the micromolar range (Binley et al., 1997); so for high-affinity binding (Kd < 10 nM), the occupancy of gp120 by Abs should approach saturation. And the titers of Abs able to inhibit the binding of gp120 to CD4 (and hence indirectly to CCR5 or CXCR4) are in the range 1:100 to 1:1000 in HIV-1+ sera (Callahan and Norcross, 1989 and Moore et al., 1994a). Thus, in the presence of undiluted HIV-1+ plasma, as occurs in vivo, there would be effectively no binding of gp120 monomers to CD4 or the co-receptors. This is rarely accounted for in the design and interpretation of in vitro studies with recombinant gp120, but it always should be.

Less complexing of gp120 by Abs would occur in some tissue locales. For example, Abs are present only at low levels in the central nervous system, even when HIV-1 infection causes intrathecal Ab production and blood–brain barrier leakage (Goudsmit et al., 1987 and Kaul et al., 2001). In general, Ab concentrations in different tissues are likely to vary considerably from those of gp120 and virus. Predicting the net effects of variations in relative and absolute concentrations of Ab, gp120 and virus is a complex task that we do not attempt here.

Concentration of gp120 in tissues

The putative levels of gp120 measured, or plausibly present, in plasma are far below some of those that have significant effects on cells in vitro. But could the latter concentrations nevertheless be biologically relevant by matching those in compartments other than blood? The gp120 concentrations in, for example, the interstitial spaces of lymph nodes or other solid organs are unknown. Nevertheless, if the greater density of cells, the smaller extracellular space and the possibly slower dilution kinetics were quantitatively factored in, it seems plausible that gp120 could be present within interstitial lymph node spaces at concentrations several orders of magnitude higher than in plasma. Furthermore, if small secluded spaces are created during cell-to-cell transmission of HIV-1 and HTLV-1, the so-called virological synapses (Igakura et al., 2003 and Jolly et al., 2004), then viral proteins may be present at high local concentrations in those clefts. In vitro studies involving Env-producing cells may, therefore, be more realistic than those using soluble, recombinant gp120 (Castedo et al., 2001; Castedo et al., 2002 and Jekle et al., 2003). However, the gp120 concentration gradients produced by such cells are difficult to assess. And membrane-associated Env may differ from soluble gp120 in, for example, its qualitative effects on T-cell activation (Schwartz et al., 1994).

Another relevant complication is that gp120 from X4 viruses, but not R5 viruses, binds to heparan-sulphate glycosoaminoglycan (GAG) moieties of proteoglycans, and thereby can be retained within tissues both in the extracellular matrix and on cell surfaces (Moulard et al., 2000 and Ugolini et al., 1999). GAGs are present on the surface of many cell types (Ugolini et al., 1999). An analogy may be drawn between gp120 and chemokines that, in vivo, do not seem to act as free proteins. Chemokines, instead, interact with G-protein-coupled receptors while in the form of surface-bound GAG complexes that establish haptotactic gradients in tissues (Proudfoot et al., 2003). Such potentially modulating effects of the tissue environment complicate the rational design and interpretation of in vitro experiments, which by necessity simulate in vivo conditions imperfectly.

We conclude that the relevant gp120 concentrations in the organism are essentially unknown.

Affinity of gp120 for its receptors and the influence of receptor occupancy

Ultimately, any consequences of local concentrations of gp120 depend on its affinity for the relevant receptors and the degree of binding required for signals to be transduced. Several effects of gp120 are mediated through CD4 binding, either directly or indirectly through subsequent CD4-dependent interactions with a chemokine coreceptor. The Kd of gp120 binding to CD4 is in the range 1–10 nM (Ashkenazi et al., 1990; Ivey-Hoyle et al., 1991; Moebius et al., 1992 and Moore, 1990). That is higher even than the concentrations reported by Oh et al. and 1000-fold higher than those found by Gilbert et al. (2003). However, gp120 may also bind with high affinity to DC-SIGN and other C-type lectin receptors (Geijtenbeek et al., 2002 and Turville et al., 2002), as well as to the GAG moieties of proteoglycans (Moulard et al., 2000 and Ugolini et al., 1999). Although the latter interactions of soluble monomeric X4 gp120 are readily reversible (Mondor et al., 1998b), binding to such accessory attachment molecules could raise the effective gp120 concentrations available for other receptor interactions.

Quite distinct degrees of binding, or occupancies, of cellular receptors may be required to exert the different effects on the target cells that we are discussing. But generally, the occupancy can be estimated from the formula [[gp120]/Kd]/[[1 + [gp120]]/Kd] (Klasse and Moore, 1996). Thus, for 99% occupancy, the concentration of gp120 must be >100-fold above Kd. That means 0.1–1 μM for CD4 binding. Indirect effects of gp120 on T-cell activation, mediated by blocking the interactions of antigen-MHC class II with CD4 and the T-cell receptor (Chirmule et al., 1995), would quite plausibly require the binding of gp120 to a large proportion of CD4 molecules. Some effects involving signaling via cell-surface receptors are, in principle, different. Thus, much lower occupancies, produced by gp120 concentrations close to or below Kd (Munshi et al., 2003) could conceivably be effective. Most biological effects would nevertheless require a detectable occupancy. Hence, we face a double conundrum: either active concentrations of gp120 are above Kd for receptor binding, which may not be realistic under in vivo conditions; or they are lower, which makes it difficult to explain how substantial binding could be achieved.

Some effects of gp120 are suggested to occur independently of CD4 (for example, Iyengar et al., 1999). The affinity of gp120 for CCR5 and CXCR4 in the absence of CD4 is usually found to fall below the limit of detection. Thus, there was no detectable X4 gp120 binding to CXCR4 at concentrations as high as 0.25–0.5 μM (Doranz et al., 1999 and Mondor et al., 1998a), and little binding of R5 gp120 to CCR5 at 0.4–0.5 μM (Trkola et al., 1996 and Wu et al., 1996). There is, however, one starkly contrasting report of higher-affinity gp120 binding (Kd ≈ 70 nM) to CXCR4 on CD4-negative, differentiated neuronal cells (Hesselgesser et al., 1997). The binding of soluble-CD4–gp120 complexes to CCR5 has a Kd of 4 nM (Doranz et al., 1999 and Wu et al., 1996), and to CXCR4 of 200 nM (Babcock et al., 2001). Despite the poor or controversial capacity of gp120 to interact directly with CCR5 or CXCR4, a pathophysiological role for the interaction of gp120 with these molecules on neurons and astrocytes has been proposed (Kaul et al., 2001). If the highest reported gp120–CXCR4 affinity is accurate (Hesselgesser et al., 1997), then the dose dependence of X4 gp120-mediated apoptotic effects via CXCR4 on CD4− neuronal cells is as expected, that is, a significant and increasing response from 20 nM to 1 μM (Hesselgesser et al., 1998). But whether that extremely high concentration range is relevant in vivo remains to be confirmed. In contrast, much lower concentrations of gp120 (0.1–200 pM) have also been found to be neurotoxic, with and without intermediary effects on Schwann and glial cells (Keswani et al., 2003 and Meucci et al., 1998). The occupancy of CXCR4 at gp120 concentrations in the sub-nanomolar range would be immeasurably low (<0.1%), even if we assume that the Kd ≈ 70 nM (Hesselgesser et al., 1997).

It is possible to investigate whether gp120 is bound to cells from HIV-1-infected individuals, and at what occupancy, ex vivo. The presence of gp120 attached to CD4 on the T-cell surface ex vivo has been inferred, although not directly detected (Amadori et al., 1992). But there is also a converse finding of the failure to detect specific masking of the gp120-binding site on CD4 on T cells from HIV-1-infected individuals (Kunkl et al., 1994). Resolving whether gp120 is detectable on the surface of CD4+ (or CD4−) cells ex vivo would help clarify gp120’s pathogenic role.

The outstanding task, then, is to assess and explain the occupancy of receptors by gp120 in vivo and what effects that has on the cells.

Use of virions in vitro

Some in vitro experiments have used virus-like particles or inactivated virions to study HIV-1-induced apoptosis, for comparison with the effects of recombinant soluble gp120 (Esser et al., 2001; Vlahakis et al., 2003 and Yao et al., 2001). When virus for this use is concentrated by several orders of magnitude, considerations apply that are similar to those for monomeric gp120: how well does the virion concentration used in vitro reflect what is present in vivo? Can virion densities rise to particularly high levels in certain locales, such as interstitial spaces in lymph nodes, and there exert the effects observed in vitro? The affinity of virions for target cells is unknown but liable to be the net outcome of two opposing influences. The receptor-interactive surfaces on the gp120 subunits are relatively inaccessible in the context of the virion-associated Env trimer, which will reduce the functional affinity of the interaction. Countering this, is the polyvalency effect of multiple trimers interacting with multiple receptors (as partly illustrated for murine leukemia virus; Yu et al., 1995). The binding of X4 virions to heparan sulphate proteoglycans on the cell surface is indeed more avid than that of monomeric gp120 (Mondor et al., 1998b).

Inactivated virus with a content of 0.4 nM of p24 (Esser et al., 2001), or even as high as 4 nM (Vlahakis et al., 2003), has been used in vitro. This corresponds to 8–80 pM virion-associated gp120. The degree of receptor binding that may ensue at these levels of virion-associated Env cannot be rationally predicted at present. But the maximal virus-induced apoptotic effect could not be mimicked by the corresponding amounts of monomeric gp120 or heat-denatured virions, and it required the presence of MHC class II on the virion (Esser et al., 2001). However, in another experimental system, HIV-1-induced cytolysis occurred regardless of the presence of MHC class II (LaBonte et al., 2003). Cytolysis is an alternative mechanism of cell death to apoptosis induced by receptors, and cytolysis are alternative mechanisms of cell death, cytolysis requires fusogenic Env protein, and affects only the infected cell (LaBonte et al., 2003).

The relative relevance of the experimental use of soluble Env, inactivated virions and fusogenic replicating virus to the pathogenesis of AIDS needs to be elucidated.

Improving the design of experiments using gp120

How could the design of in vitro studies using monomeric gp120 be improved (see Box 1)? The possible presence of biologically active contaminants, including endotoxins in gp120 preparations from commercial and other sources should always be considered. The use of anti-gp120 MAbs specifically to prevent gp120-CD4 or -coreceptor binding is a prudent control. As noted above, HIV-1+ serum antibodies will have much the same effect as the specific MAbs, and their presence in vivo must be taken into account. Gp120 point mutants defective for CD4 or coreceptor binding provide further controls. Thereby one can at least determine whether the consequences of sprinkling gp120 on mammalian cells depend on receptor binding, or whether they are merely attributable to contaminants in the protein preparation.

Conclusions

We do not argue that gp120 could never have a biological effect on cells in vivo via receptor-mediated interactions. Nor is it impossible that virions could influence cellular processes in vivo independently of receptor-mediated fusion events.

We do, however, argue that it is not an adequate mimic of in vivo biology simply to add free gp120 (or virions) to target cells in vitro in amounts that are apparently several orders of magnitude greater than in body fluids. Moreover, it is not appropriate to justify the amounts of gp120 used by reference to the two decade-old papers that purport to measure free gp120 in the plasma of HIV-1-infected people. These papers are not consistent with each other, and the more frequently cited study, by Oh et al., has serious design flaws that may cast doubt on the gp120 concentrations it promulgates. The much lower gp120 concentrations recorded by Gilbert et al. (2003) are likely to be closer to true levels. And the presence of plasma anti-gp120 Abs that block receptor binding should inform the design of in vitro experiments (see Box 1). Controls for gp120 purity and for the specificity of the interactions with CD4, chemokine receptors and GAGs should also be included in experimental protocols. Some of these considerations apply, of course, to other studies of similar design that use high concentrations of other HIV-1 proteins, such as Tat and Vpr, in vitro, in the hope that this is relevant to pathogenesis.

Box 1. Criteria for establishing the biological relevance of experiments using gp120 in vitro

1. Experimental concentration ranges shown to be relevant to the particular tissue compartment modeled.
2. Specificity of the receptor interactions demonstrated by use of gp120 deletion mutants or Abs blocking receptor binding.
3. Demonstration that the requisite receptor occupancy can be obtained under experimental conditions.
4. Inclusion of anti-gp120 Abs with a binding capacity (concentration and affinity) corresponding to that in the relevant tissue compartment.
5. Comparison of effects of recombinant gp120 with those of realistic levels of virions.

Acknowledgements

We are grateful to Maciej Paluch for preparation of the illustrations and to André Marozsan for discussions. This work was supported by NIH grants AI36082, AI39420 and AI41420. J.P.M. is a Stavros S. Niarchos Scholar. The Department of Microbiology and Immunology at the Weill Medical College gratefully acknowledges the support of the William Randolph Hearst Foundation.

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Corresponding author. Joan and Sanford I. Weill Medical College of Cornell University, Department of Microbiology and Immunology, 1300 York Avenue, W-805, New York, NY 10021. Fax: +1-212-746-8340.

Virology
Volume 323, Issue 1, 20 May 2004, Pages 1-8
Copyright © 2007 Elsevier B.V. All rights reserved.

Oprah’s incredible Xmas journey

December 25th, 2006


Replay of South African trip rekindles joy in hearts of audience

But does “AIDS” mean only one treatment?

Oprah visited South Africa about two years ago, and celebrated Christmas by rerunning the segment this Christmas Day.

She gave clothes to poor children there, who were quite transformed by the simple gifts, which were the only decent costume they had had for quite a while, if ever. The joy that broke out in the hall was ecstatic. Children ran to hug Oprah and say “I love you Oprah”. “I love you too”, Oprah replied. She also handed out each child a box with packaged food for a month. Afterwards she broke out in loud sobs, as she walked away from the event.

((Click pics twice for maximum enlargement)).

She then visited the home of a (soon to be) AIDS orphan and then went with her to the mother lying in the hospital, hollow eyed, one eye grotesquely larger than the other, with “AIDS”, although the public hospital had no drugs to treat her, because the government had not provided any, the black doctor explained to Oprah.

Oprah broke down at this and cried in public, sobbing “I don’t understand it. I don’t understand it.” When she finished sobbing, she hugged the child for a long moment that the cameras caught in full.

Later, she tells us that she has now discovered her purpose in life, and the reason why she has never married. It is to use her voice to rescue the children of South Africa from the rural sex orgy spreading HIV among their parents.

Now, she reports from stage today, the government has agreed to supply drugs. She wants you to find the same joy in giving by doing something for these people, whose country has more people with AIDS than any other. You can contribute to her “Angel Network” which presumably will send more drugs.

Question: If the woman was not treated for AIDS, was she treated for anything else? The doctor told Oprah she was treated for her symptoms, but the response seemed to be only acquiescence to Oprah’s question in this regard. So evidently what was meant was any symptoms were alleviated as far as possible.

The mother subsequently died. If she died of TB, was she treated for TB, or not? Presumably not effectively. Why not? is there a shortage of antibiotics or whatever cures TB, or is African TB too lethal in poor people? It certainly is rampant in Africa, and a new strain is said to be causing new problems.

Bottom line: Does the diagnosis of supposed AIDS mean that they don’t bother to give a mother any antibiotics? Surely not.

But one suspects that this is a possibility. Once “AIDS” is the diagnosis, the assumption of everybody involved is that only Western drugs can save the patient.

Certainly this is the assumption of all viewers of this segment, which follows a repeat of Oprah’s “Buy Red with Bono” show a couple of weeks ago.

At this rate Dr Anthony Fauci is probably in love with Oprah, who has become the largest propaganda spokesman for the standard wisdom in AIDS short of WHO.

Audience: 7 million or more.

Duesberg triumphant at Rockwell Conference

December 5th, 2006


Surrounded by admirers for two hours, the celebrated HIV∫AIDS critic is birthday boy

But no one offers a check – yet

Just how well Duesberg’s talk went at the Libertarian Lew Rockwell conference in San Francisco on Friday and Saturday, where Duesberg delivered the keynote on Friday evening at 6.30pm, “AIDS – a viral or chemical epidemic?”, is made clear on Barnesworld, the blog renamed Hank’s You Bet Your Life, where two appreciative reports are carried today. They give a good account of both the scene and the content of Duesberg’s talk to about 150 people.

Duesberg was surrounded by a throng of questioners for two hours afterwards, during which a birthday cake was carried in in his honor, December 2 being his 70th birthday (”he looks 50″ says one of the entries). Scholar and author Harvey Bialy, the eminence grise of the blog and now its frequent correspondent, follows the reports with an email from Duesberg which ends with the single down note (as far as we are concerned) of the evening, his joke that “they did offer heart-felt applause and questions from 9 until 11 PM. But no one has asked if they could write a check to the lab yet.”

In the Comments that follow, however, there is already one Pat Edmonson promising Duesberg a share of a sum he will receive after the year end.

Carrying these reports on YBYL is a significant public service, not only because it shows how overwhelming Duesberg’s critique is when presented to a live audience, but draws attention to the key factor – big money – which has crippled good science in this field, and allow bad science to triumph. Everything is being done, we hope, to make contributions to Duesberg as easy as a click on PayPal or mailing a check. His website is Peter Duesberg, where it lists his address as Professor Peter H. Duesberg, Ph.D., Department of Molecular & Cell Biology, c/o Stanley/Donner Administrative Services Unit, 229 Stanley Hall #3206, University of California at Berkeley, Berkeley, CA 94720-3206 Fax: (510) 643-6455. There is a form to write a quick email to Duesberg if you wish at Write an email.

Why send money to Duesberg?

His research into cancer is the most significant and pioneering in the field, and can be continued at the modest sum of $100,000 a year. Modest, that is, relative to the huge sums being wasted by proponents of the current oncogene paradigm in cancer research, which Duesberg and Bialy have pointed out in their respective articles and books has been a theoretical dead end since the mid eighties, like HIV∫AIDS, an even vaster money machine which is also wasting all its research millions on a paradigm which has yet to be justified in any meaningful way, not to mention wasting the expanding millions spent on delivering AIDS drugs to patients here and in Africa, India and points East, courtesy of the efforts of Gates, Clinton, Bono and other celebrities whose view of HIV∫AIDS is under researched.

At the moment, with his faithful long time lab assistant dying of the very same dread disease that they were researching, Duesberg is alone in his laboratory, dealing with his own minor errands and bench work as well as following his fruitful intellectual path into exploring aneuploidy (multiplying chromosomes) as the real trigger of cancer, as explained in Harvey Bialy’s valuable handbook to the Duesberg saga in both fields, “Oncogenes, Aneuploidy and AIDS: A Scientific Life of Peter H. Duesberg”.

There have been no graduate students in Berkeley who have dared work under Duesberg since he entered the fray by tilting against both the HIV∫AIDS and oncogene windmills two decades ago in Cancer Research. But the undergraduates he taught about viruses and cancer last year gave him a standing ovation after his final class.

All in all, there are few scientists who deserve full funding more than Duesberg, given the staggering quality and significance of his accomplishments, from starting two major fields of research (oncogenes and aneuploidy) to renouncing two (oncogenes and HIV∫AIDS) out of a love of real scientific truth and a sense of public responsibility, despite his privileges as the leading scientist in oncogenes and retroviruses and popularity among the scientific elite – he was a member of the National Academy before any of his opponents in AIDS, as far as we know, and every single grant application of his to the NIH was given the green light, until he wrote the Cancer Research paper in 1987 rejecting HIV as the cause of AIDS.

His work over twenty two years dealing with the profession and the public on the HIV∫AIDS question is a breathtaking accomplishment given the depth and breadth of the research he had to cover to shut all the escape hatches built by the paradigm promoters in arguing that even if the theory didn’t make too much sense in this regard or that regard it would all become clear in the end.

Meanwhile they need another $100 million from the NIH, please, whereas all the time Duesberg’s important research in cancer was shortchanged of his time and starved of funds, since Duesberg has never got a penny from the NIH since 1987 and the number of private patrons who have responded you can count in the fingers of one hand and have two fingers left over, and this in a country where there are now so many millionaires that only billionaires are counted as rich any more. San Francisco private investor Robert Leppo deserves a medal for taking the lead in enabling Duesberg’s work.

ABC’s John Stossel ran a segment last Wednesday taking the super rich to task for not contributing enough to charity, and we were particularly struck by the man worth $6 billion who said he didn’t know where to send it.

We are sending him a suggestion.

Duesberg, hero of AIDS, speaks today

December 1st, 2006


Talk by Berkeley scientist, public spirited conqueror of doubt and confusion in HIV∫AIDS madness

First annual award of NAR goes to indomitable scientist

We have just learned rather belatedly from our brother in arms blog, the high level Hank’s You Bet Your Life directed by Harvey Bialy that Peter Duesberg is to speak tonight (Fri Dec 1) in San Francisco. Go to Lew Rockwell and the Libertarians Celebrate World AIDS Day with Peter Duesberg to read about it, and download Duesberg’s powerpoint presentation which will be put up during today, and a live report before and after the talk.

The cost will be $150 and in our opinion, well worth it, especially for anyone who has never seen this restlessly sharp and witty analyst in action. A lecture by Duesberg is a live event that lives up to the description, for his style is entirely spontaneous, even if he is delivering slides and comment he has covered before. The only problem is that sometimes his witticisms at the expense of dull mediocrity are delivered in a conversational throwaway giggle, rather than in the ringing tones they deserve.

Come to the LRC Conference!“May you be Healthy, Wealthy and Wise.” That’s about as generous a wish one person can offer another. Well, you’re on the way if you attend the LRC Benefit Conference on revisionist health and finances on December 1–2, 2006 at the Crowne Plaza Hotel in Foster City, California, near the San Francisco Airport. Join us. You’ll be dazzled by our speakers, have a terrific time and help LRC as well.

Friday, December 1, Marco Polo Room

* 5:30pm: Registration and Welcome 6:00pm:

* Burt Blumert, Center for Libertarian Studies Mark Thornton, Ludwig von Mises Institute “Welcome”

* 6:15pm: Gary North, “Dr. Rothbard’s Prescription for Health and Wealth”

* 6:45pm: Peter Duesberg, University of California at Berkeley “Is AIDS a Viral or a Chemical Epidemic? – a Multi-Billion-Dollar Question”

* 7:15pm: Gala Reception

Presumably Duesberg’s presentation will be the one he gave at the meeting in New York in June, when he addressed the Rethinking AIDS group meeting and the press on the topic of how HIV∫AIDS scientists and officials have failed to realize any of the predictions inherent in their favorite paradigm, from heterosexual spread in the US to a rise and fall in prevalence in the US to virus killing T cells to significant mortality globally, while Duesberg’s alternative account of AIDS, as an immune deficit syndrome caused by drugs in the US and conventional assaults such as malnutrition and diseases in Africa, predicts everything that has happened in this field over the last two decades quite beautifully.

Peter Duesberg wins first annual NAR “Hero of AIDS”award

The Duesberg presentation on World AIDS Day coincides happily with the decision of the editors, writers and researchers of New AIDS Review to award its first annual Hero of AIDS medal to the distinguished pioneering scientist.

Other scientists in the running for the award included Robert Gallo, the first man to entirely disprove his own fervent hope that HIV was the “probable cause of AIDS”, as he and Margaret Heckler announced in 1994 at a press conference faithfully transmitted to the front page of the New York Times and thence worldwide by Lawrence K. Altman, the MD and CDC trainee on whom the Times has since depended for its unvarying support of this notion of HIV as “the virus that causes AIDS”, even though as it turned out a week later Gallo’s heralded papers in Science revealed that HIV was not the cause of AIDS after all, since he had been able to find it in only 26 out of 72 patients’ blood samples.

Also considered was Dr Anthony Fauci, Director of NIAID at the NIH, who was the first to bring the attention of scientists to the fact that HIV not only did not kill T cells in a provable manner that anyone understood, either directly or indirectly, but actually provoked the proliferation of CD4 T cells, the very cells it was meant to kill directly or indirectly, or by supernatural means, and thus cause AIDS through immune dysfunction. This didn’t provably happen.

Instead, the implication from the pen of this giant of science running NIAID was that the answer to AIDS might be infecting patients with more HIV, normally absent from their bodies in any detectable amount, which like any good leukemia virus (human T cell leukemia virus was Gallo’s first name for HIV) would not only augment the CD4 count of patients, but also act as a vaccine to ensure that they were better defended against HIV by multiplying antibodies to it, so there will be even less HIV in patients than the normal vanishing amount. In other words, the correct antidote to HIV was more HIV.

However, neither of these scientists have had the courage of Peter Duesberg in bringing their conclusions to the attention of the public as well as of scientists, so we unanimously decided that Duesberg was the first and only choice for the first award of Hero of AIDS for his work over two decades demonstrating that Gallo was correct, and there is no chance in Hades that HIV is the cause of anything, let alone AIDS.

The following is the full rationale attached to the award, which will be presented to Duesberg in person when he is next in New York:

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